Updated on 2021/12/07

写真a

 
KANAUCHI Satoko
 
Organization
Graduate School of Medicine Designated associate professor
Title
Designated associate professor

Degree 1

  1. 博士(工学) ( 2006.9   埼玉大学 ) 

Research History 1

  1. Nagoya University   School of Medicine   Designated associate professor

    2021.4

Awards 1

  1. 理研栄峰賞

    2020.3   国立研究開発法人理化学研究所   AIによる内視鏡画像からの早期胃がん領域の高精度自動検出法の研究開発

    横田秀夫、竹本智子、坂井良匡

 

Papers 33

  1. Detecting colon polyps in endoscopic images using artificial intelligence constructed with automated collection of annotated images from an endoscopy reporting system. Reviewed International journal

    Keisuke Hori, Hiroaki Ikematsu, Yoichi Yamamoto, Hiroki Matsuzaki, Nobuyoshi Takeshita, Kensuke Shinmura, Yusuke Yoda, Takayoshi Kiuchi, Satoko Takemoto, Hideo Yokota, Tomonori Yano

    Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society     2021.11

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    Language:English   Publishing type:Research paper (scientific journal)  

    BACKGROUND: Artificial intelligence (AI) has made considerable progress in image recognition, especially in the analysis of endoscopic images. The availability of large-scale annotated datasets has contributed to the recent progress in this field. Datasets of high-quality annotated endoscopic images are widely available, particularly in Japan. A system for collecting annotated data reported daily could aid in accumulating a significant number of high-quality annotated datasets. AIM: We assessed the validity of using daily annotated endoscopic images in a constructed reporting system for a prototype AI model for polyp detection. METHODS: We constructed an automated collection system for daily annotated datasets from an endoscopy reporting system. The key images were selected and annotated for each cases only during daily practice, not to be performed retrospectively. And we automatically extracted annotated endoscopic images of diminutive colon polyps that had been diagnosed (study period: March- September 2018) using the keywords of diagnostic information, and additionally collect the normal colon images. The collected dataset was devised into training and validation to build and evaluate the AI system. The detection model was developed using a deep learning algorithm, RetinaNet. RESULTS: The automated system collected endoscopic images (47,391) from colonoscopies (745), and extracted key colon polyp images (1356) with localized annotations. The sensitivity, specificity, and accuracy of our AI model were 97.0%, 97.7%, and 97.3% (n = 300), respectively. CONCLUSION: The automated system enabled the development of a high-performance colon polyp detector using images in endoscopy reporting system without the efforts of retrospective annotation works.

    DOI: 10.1111/den.14185

    PubMed

  2. 画像処理による細胞集団の形態と機能の定量解析 Invited

    竹本 智子, 吉澤 信, 山下 典理男, 森田 正彦, 西村 将臣, 横田 秀夫

      Vol. 56 ( 4 ) page: 423 - 431   2021.9

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    Authorship:Lead author   Language:Japanese   Publishing type:Research paper (scientific journal)  

  3. 胃疾患におけるAI診断:高効率な学習スキームによる胃癌の領域検出AI Invited Reviewed

    堀 圭介, 竹本 智子, 横田 秀夫, 池松 弘朗, 矢野 友規

    胃と腸   Vol. 56 ( 4 ) page: 423 - 431   2021.4

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    Language:Japanese   Publishing type:Research paper (scientific journal)  

    DOI: https://doi.org/10.11477/mf.1403202297

  4. Accurate and fast mitotic detection using an anchor-free method based on full-scale connection with recurrent deep layer aggregation in 4D microscopy images Reviewed

    T. Kitrungrotsakul, Y. Iwamoto, S. Takemoto, H. Yokota, S. Ipponjima, T. Nemoto, L. Lin, R. Tong, J. Li, and Y.-W. Chen

    BMC Bioinformatics   Vol. 22 ( 91 ) page: 1 - 17   2021.2

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: https://doi.org/10.1186/s12859-021-04014-w

  5. A Cascade of 2.5D CNN and Bidirectional CLSTM Network for Mitotic Cell Detection in 4D Microscopy Image. Invited

    Titinunt Kitrungrotsakul, Xian-Hua Han, Yutaro Iwamoto, Satoko Takemoto, Hideo Yokota, Sari Ipponjima, Tomomi Nemoto, Wei Xiong 0001, Yen-Wei Chen 0001

    IEEE ACM Trans. Comput. Biol. Bioinform.   Vol. 18 ( 2 ) page: 396 - 404   2021

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1109/TCBB.2019.2919015

    PubMed

  6. Accurate and fast mitotic detection using an anchor-free method based on full-scale connection with recurrent deep layer aggregation in 4D microscopy images. Reviewed International journal

    Titinunt Kitrungrotsakul, Yutaro Iwamoto, Satoko Takemoto, Hideo Yokota, Sari Ipponjima, Tomomi Nemoto, Lanfen Lin, Ruofeng Tong 0001, Jingsong Li, Yen-Wei Chen 0001

    BMC Bioinform.   Vol. 22 ( 1 ) page: 91 - 91   2021

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    Language:English   Publishing type:Research paper (scientific journal)  

    BACKGROUND: To effectively detect and investigate various cell-related diseases, it is essential to understand cell behaviour. The ability to detection mitotic cells is a fundamental step in diagnosing cell-related diseases. Convolutional neural networks (CNNs) have been successfully applied to object detection tasks, however, when applied to mitotic cell detection, most existing methods generate high false-positive rates due to the complex characteristics that differentiate normal cells from mitotic cells. Cell size and orientation variations in each stage make detecting mitotic cells difficult in 2D approaches. Therefore, effective extraction of the spatial and temporal features from mitotic data is an important and challenging task. The computational time required for detection is another major concern for mitotic detection in 4D microscopic images. RESULTS: In this paper, we propose a backbone feature extraction network named full scale connected recurrent deep layer aggregation (RDLA++) for anchor-free mitotic detection. We utilize a 2.5D method that includes 3D spatial information extracted from several 2D images from neighbouring slices that form a multi-stream input. CONCLUSIONS: Our proposed technique addresses the scale variation problem and can efficiently extract spatial and temporal features from 4D microscopic images, resulting in improved detection accuracy and reduced computation time compared with those of other state-of-the-art methods.

    DOI: 10.1186/s12859-021-04014-w

    PubMed

  7. An end-to-end CNN and LSTM network with 3D anchors for mitotic cell detection in 4D microscopic images and its parallel implementation on multiple GPUs. Reviewed

    Titinunt Kitrungrotsakul, Xian-Hua Han, Yutaro Iwamoto, Satoko Takemoto, Hideo Yokota, Sari Ipponjima, Tomomi Nemoto, Wei Xiong 0001, Yen-Wei Chen 0001

    Neural Comput. Appl.   Vol. 32 ( 10 ) page: 5669 - 5679   2020

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    Publishing type:Research paper (scientific journal)  

    DOI: 10.1007/s00521-019-04374-8

  8. CNNによる少数教師データからの早期胃がん領域の検出 Invited

    竹本 智子, 堀 圭介,坂井 良匡,西村 将臣,池松 弘朗,矢野 友規,横田 秀夫

    精密工学会誌   Vol. 85 ( 9 ) page: 761 - 764   2019.9

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    Language:Japanese  

  9. An end-to-end CNN and LSTM network with 3D anchors for mitotic cell detection in 4D microscopic images and its parallel implementation on multiple GPUs Invited Reviewed

    T. Kitrungrotsakul, X.-X Han, Y. Iwamoto, S. Takemoto, H. Yokota, S. Ipponjima, T. Nemoto, X. Wei, and Y.-W. Chen

    Neural Computing and Applications   Vol. 32   page: 5669 - 5679   2019.8

  10. ViBrism DB: an interactive search and viewer platform for 2D/3D anatomical images of gene expression and co-expression networks Reviewed

    M. Morita, K. Shimokawa, M. Nishimura, S. Nakamura, Y. Tsujimura, S. Takemoto, T. Tawara, H. Yokota, S. Wemler, D. Miyamoto, H. Ikeno, A. Sato, T. Furuichi, N. Kobayashi, Y. Okumura, Y. Yamaguchi, Y. Okamura-Oho

    Nucleic Acids Research   Vol. 47 ( D1 ) page: D859 - D866   2019.1

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    Language:Japanese  

    DOI: https://doi.org/10.1093/nar/gky951

  11. A Cascade of CNN and LSTM Network with 3D Anchors for Mitotic Cell Detection in 4D Microscopic Image. Reviewed International journal

    Titinunt Kitrungrotsakul, Yutaro Iwamoto, Xian-Hua Han, Satoko Takemoto, Hideo Yokota, Sari Ipponjima, Tomomi Nemoto, Xiong Wei 0001, Yen-Wei Chen 0001

    IEEE/ACM transactions on computational biology and bioinformatics     page: 1239 - 1243   2019

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    Language:English   Publishing type:Research paper (scientific journal)  

    Mitosis detection is one of the challenging steps in biomedical imaging research, which can be used to observe the cell behavior. Most of the already existing methods that are applied in detecting mitosis usually contain many nonmitotic events (normal cell and background) in the result (false positives, FPs). In order to address such problem, in this study, we propose to apply 2.5-dimensional (2.5D) networks called CasDetNet_CLSTM, which can accurately detect mitotic events in 4D microscopic images. This CasDetNet_CLSTM involves a 2.5D faster region-based convolutional neural network (Faster R-CNN) as the first network, and a convolutional long short-term memory (CLSTM) network as the second network. The first network is used to select candidate cells using the information from nearby slices, whereas the second network uses temporal information to eliminate FPs and refine the result of the first network. Our experiment shows that the precision and recall of our networks yield better results than those of other state-of-the-art methods.

    DOI: 10.1109/ICASSP.2019.8682326

    PubMed

    Other Link: https://dblp.uni-trier.de/db/conf/icassp/icassp2019.html#Kitrungrotsakul19

  12. ViBrism DB: an interactive search and viewer platform for 2D/3D anatomical images of gene expression and co-expression networks. Reviewed International journal

    Masahiko Morita, Kazuro Shimokawa, Masaomi Nishimura, Sakiko Nakamura, Yuki Tsujimura, Satoko Takemoto, Takehiro Tawara, Hideo Yokota, Shuhei Wemler, Daisuke Miyamoto, Hidetoshi Ikeno, Akira Sato, Teiichi Furuichi, Norio Kobayashi, Yoshihiro Okumura, Yoko Shiraishi-Yamaguchi, Yuko Okamura-Oho

    Nucleic Acids Res.   Vol. 47 ( Database-Issue ) page: D859-D866 - 866   2019

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    Language:English   Publishing type:Research paper (scientific journal)  

    Understanding anatomical structures and biological functions based on gene expression is critical in a systemic approach to address the complexity of the mammalian brain, where >25 000 genes are expressed in a precise manner. Co-expressed genes are thought to regulate cell type- or region-specific brain functions. Thus, well-designed data acquisition and visualization systems for profiling combinatorial gene expression in relation to anatomical structures are crucial. To this purpose, using our techniques of microtomy-based gene expression measurements and WebGL-based visualization programs, we mapped spatial expression densities of genome-wide transcripts to the 3D coordinates of mouse brains at four post-natal stages, and built a database, ViBrism DB (http://vibrism.neuroinf.jp/). With the DB platform, users can access a total of 172 022 expression maps of transcripts, including coding, non-coding and lncRNAs in the whole context of 3D magnetic resonance (MR) images. Co-expression of transcripts is represented in the image space and in topological network graphs. In situ hybridization images and anatomical area maps are browsable in the same space of 3D expression maps using a new browser-based 2D/3D viewer, BAH viewer. Created images are shareable using URLs, including scene-setting parameters. The DB has multiple links and is expandable by community activity.

    DOI: 10.1093/nar/gky951

    PubMed

    Other Link: https://dblp.uni-trier.de/db/journals/nar/nar47.html#MoritaSNNTTTYWM19

  13. THE DIAGNOSTIC ARTIFICIAL INTELLIGENCE (AI) SYSTEM FOR DETECTION OF COLON POLYPS WITH HIGH EFFICIENCY OF DEEP LEARNING Reviewed

    Hori Keisuke, Ikematsu Hiroaki, Shinmura Kensuke, Yoda Yusuke, Oono Yasuhiro, Takemoto Satoko, Yokota Hideo, Yano Tomonori

    GASTROINTESTINAL ENDOSCOPY   Vol. 87 ( 6 ) page: AB240 - AB241   2018.6

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  14. A 2.5D Cascaded Convolutional Neural Network with Temporal Information for Automatic Mitotic Cell Detection in 4D Microscopic Images. Reviewed

    Titinunt Kitrungrotsakul, Xian-Hua Han, Yutaro Iwamoto, Satoko Takemoto, Hideo Yokota, Sari Ipponjima, Tomomi Nemoto, Xiong Wei 0001, Yen-Wei Chen 0001

    CoRR   Vol. abs/1806.01018   page: 202 - 205   2018

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    Publishing type:Research paper (international conference proceedings)  

    In recent years, intravital skin imaging has been increasingly used in<br />
    mammalian skin research to investigate cell behaviors. A fundamental step of<br />
    the investigation is mitotic cell (cell division) detection. Because of the<br />
    complex backgrounds (normal cells), the majority of the existing methods cause<br />
    several false positives. In this paper, we proposed a 2.5D cascaded end-to-end<br />
    convolutional neural network (CasDetNet) with temporal information to<br />
    accurately detect automatic mitotic cell in 4D microscopic images with few<br />
    training data. The CasDetNet consists of two 2.5D networks. The first one is<br />
    used for detecting candidate cells with only volume information and the second<br />
    one, containing temporal information, for reducing false positive and adding<br />
    mitotic cells that were missed in the first step. The experimental results show<br />
    that our CasDetNet can achieve higher precision and recall compared to other<br />
    state-of-the-art methods.

    DOI: 10.1109/FSKD.2018.8687125

    arXiv

    Other Link: https://dblp.uni-trier.de/db/conf/icnc/icnc2018.html#Kitrungrotsakul18

  15. Automatic detection of early gastric cancer in endoscopic images using a transferring convolutional neural network. Reviewed

    Yoshimasa Sakai, Satoko Takemoto, Keisuke Hori, Masaomi Nishimura, Hiroaki Ikematsu, Tomonori Yano, Hideo Yokota

    Conf Proc IEEE Eng Med Biol Soc   Vol. 2018   page: 4138 - 4141   2018

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    Language:English   Publishing type:Research paper (international conference proceedings)  

    DOI: 10.1109/EMBC.2018.8513274

    PubMed

    Other Link: https://dblp.uni-trier.de/conf/embc/2018

  16. A Cascade of 2.5D CNN and LSTM Network for Mitotic Cell Detection in 4D Microscopy Image. Reviewed

    Titinunt Kitrungrotsakul, Xian-Hua Han, Yutaro Iwamoto, Satoko Takemoto, Hideo Yokota, Sari Ipponjima, Tomomi Nemoto, Wei Xiong 0001, Yen-Wei Chen 0001

    CoRR   Vol. abs/1806.01018   2018

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    Publishing type:Research paper (scientific journal)  

    Other Link: https://dblp.uni-trier.de/db/journals/corr/corr1806.html#abs-1806-01018

  17. A statistical image analysis framework for pore-free islands derived from heterogeneity distribution of nuclear pore complexes. Reviewed International journal

    Yasuhiro Mimura, Satoko Takemoto, Taro Tachibana, Yutaka Ogawa, Masaomi Nishimura, Hideo Yokota, Naoko Imamoto

    Scientific reports   Vol. 7 ( 1 ) page: 16315 - 16315   2017.11

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:NATURE PUBLISHING GROUP  

    Nuclear pore complexes (NPCs) maintain cellular homeostasis by mediating nucleocytoplasmic transport. Although cyclin-dependent kinases (CDKs) regulate NPC assembly in interphase, the location of NPC assembly on the nuclear envelope is not clear. CDKs also regulate the disappearance of pore-free islands, which are nuclear envelope subdomains; this subdomain gradually disappears with increase in homogeneity of the NPC in response to CDK activity. However, a causal relationship between pore-free islands and NPC assembly remains unclear. Here, we elucidated mechanisms underlying NPC assembly from a new perspective by focusing on pore-free islands. We proposed a novel framework for image-based analysis to automatically determine the detailed 'landscape' of pore-free islands from a large quantity of images, leading to the identification of NPC intermediates that appear in pore-free islands with increased frequency in response to CDK activity. Comparison of the spatial distribution between simulated and the observed NPC intermediates within pore-free islands showed that their distribution was spatially biased. These results suggested that the disappearance of pore-free islands is highly related to de novo NPC assembly and indicated the existence of specific regulatory mechanisms for the spatial arrangement of NPC assembly on nuclear envelopes.

    DOI: 10.1038/s41598-017-16386-2

    Web of Science

    PubMed

  18. Analysis of the equine ovarian structure during the first twelve months of life by three-dimensional internal structure microscopy. Reviewed

    Mamiko Ono, Hiroki Akuzawa, Yasuo Nambo, Yuuko Hirano, Junpei Kimura, Satoko Takemoto, Sakiko Nakamura, Hideo Yokota, Ryutaro Himeno, Tohru Higuchi, Tadatoshi Ohtaki, Shigehisa Tsumagari

    The Journal of veterinary medical science   Vol. 77 ( 12 ) page: 1599 - 603   2016.1

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:JAPAN SOC VET SCI  

    A three-dimensional internal structure microscopy (3D-ISM) can clarify the anatomical arrangement of internal structures of equine ovaries. In this study, morphological changes of the equine ovary over the first 12 months of life were investigated by 3D-ISM in 59 fillies and by histological analysis in 2 fillies. The weight and volume of the paired ovaries initially decreased from 0 to 1 months to 2 to 3 months of age and then significantly increased at 8 to 12 months of age. The ovulation fossa was first observed around the 3rd month and became evident after the 6th month. The number of follicles with a diameter of ≥10 mm and the diameter of the largest follicle increased gradually after 6 months of age. On a volume basis, the medulla accounted for nearly 90% of the whole ovary at 0 to 1 months of age, but significantly decreased from 2 to 3 months of age. The volume of the cortex increased progressively after birth and reached approximately 60% of the total volume at 8 to 12 months of age. This significant development of the cortex coincided with the increased number and size of large follicles observed from 6 months of age. These results suggest that the development of the cortex plays a role in the maturation of the follicles and the equine ovary undergoes substantial morphological changes postnatally until puberty.

    DOI: 10.1292/jvms.14-0539

    Web of Science

    PubMed

  19. Broad integration of expression maps and co-expression networks compassing novel gene functions in the brain. Reviewed International journal

    Yuko Okamura-Oho, Kazuro Shimokawa, Masaomi Nishimura, Satoko Takemoto, Akira Sato, Teiichi Furuichi, Hideo Yokota

    Scientific reports   Vol. 4   page: 6969 - 6969   2014.11

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:NATURE PUBLISHING GROUP  

    Using a recently invented technique for gene expression mapping in the whole-anatomy context, termed transcriptome tomography, we have generated a dataset of 36,000 maps of overall gene expression in the adult-mouse brain. Here, using an informatics approach, we identified a broad co-expression network that follows an inverse power law and is rich in functional interaction and gene-ontology terms. Our framework for the integrated analysis of expression maps and graphs of co-expression networks revealed that groups of combinatorially expressed genes, which regulate cell differentiation during development, were present in the adult brain and each of these groups was associated with a discrete cell types. These groups included non-coding genes of unknown function. We found that these genes specifically linked developmentally conserved groups in the network. A previously unrecognized robust expression pattern covering the whole brain was related to the molecular anatomy of key biological processes occurring in particular areas.

    DOI: 10.1038/srep06969

    Web of Science

    PubMed

  20. A Novel Performance Evaluation System for Fluorescent Cell Image Segmentation. Reviewed

    Satoko Takemoto, Shin Yoshizawa 0001, Yuki Tsujimura, Hideo Yokota

    Proceedings - 2013 1st International Symposium on Computing and Networking, CANDAR 2013     page: 294 - 299   2013

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE Computer Society  

    Image segmentation is crucial to modern cell biology which depends on quantitative analysis of fluorescent microscopy images. Segmented regions are useful to estimate localization and dynamics of cells and sub-cellular objects. Although many segmentation algorithms have been proposed in image processing and pattern recognition fields, most approaches are designed for some specific tasks and may not work well for other tasks. This makes it difficult to find an algorithm suitable for a given task for biologists who do not have knowledge about segmentation algorithms. Automatic selection of an appropriate segmentation algorithm including its parameters efficiently has become a very important duty, since recent advances in cell and sub-cellular imaging technology significantly increases a number of observed images for biologists. In this paper, we propose a novel segmentation system which has the function of performance evaluation. The set of candidate algorithms including parameter variation are automatically generated by using combinations of the prescribed image processing methods implemented in our system, and the system is designed in order to add and replace these algorithms easily. Their segmentation qualities are evaluated by comparing each result with the ground-truth provided by biologists based on either a single or multiple similarity metrics. Finally, our system predicts which algorithm will provide the best performance on a set of images similar to the original image with ground-truth reference. We examine our system using typical segmentation algorithms under several evaluation metrics and find it useful especially for detection of fluorescent labeled targets with granular shapes on real sub-cellular images, as well as simulated images with small sub-cellular objects. © 2013 IEEE.

    DOI: 10.1109/CANDAR.2013.51

    Web of Science

    Scopus

    Other Link: https://dblp.uni-trier.de/db/conf/ic-nc/candar2013.html#TakemotoYTY13

  21. Local nucleosome dynamics facilitate chromatin accessibility in living mammalian cells. Reviewed International journal

    Saera Hihara, Chan-Gi Pack, Kazunari Kaizu, Tomomi Tani, Tomo Hanafusa, Tadasu Nozaki, Satoko Takemoto, Tomohiko Yoshimi, Hideo Yokota, Naoko Imamoto, Yasushi Sako, Masataka Kinjo, Koichi Takahashi, Takeharu Nagai, Kazuhiro Maeshima

    Cell reports   Vol. 2 ( 6 ) page: 1645 - 56   2012.12

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:CELL PRESS  

    Genome information, which is three-dimensionally organized within cells as chromatin, is searched and read by various proteins for diverse cell functions. Although how the protein factors find their targets remains unclear, the dynamic and flexible nature of chromatin is likely crucial. Using a combined approach of fluorescence correlation spectroscopy, single-nucleosome imaging, and Monte Carlo computer simulations, we demonstrate local chromatin dynamics in living mammalian cells. We show that similar to interphase chromatin, dense mitotic chromosomes also have considerable chromatin accessibility. For both interphase and mitotic chromatin, we observed local fluctuation of individual nucleosomes (~50 nm movement/30 ms), which is caused by confined Brownian motion. Inhibition of these local dynamics by crosslinking impaired accessibility in the dense chromatin regions. Our findings show that local nucleosome dynamics drive chromatin accessibility. We propose that this local nucleosome fluctuation is the basis for scanning genome information.

    DOI: 10.1016/j.celrep.2012.11.008

    Web of Science

    PubMed

  22. Transcriptome tomography for brain analysis in the web-accessible anatomical space. Reviewed International journal

    Yuko Okamura-Oho, Kazuro Shimokawa, Satoko Takemoto, Asami Hirakiyama, Sakiko Nakamura, Yuki Tsujimura, Masaomi Nishimura, Takeya Kasukawa, Koh-hei Masumoto, Itoshi Nikaido, Yasufumi Shigeyoshi, Hiroki R Ueda, Gang Song, James Gee, Ryutaro Himeno, Hideo Yokota

    PloS one   Vol. 7 ( 9 ) page: e45373   2012

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:PUBLIC LIBRARY SCIENCE  

    Increased information on the encoded mammalian genome is expected to facilitate an integrated understanding of complex anatomical structure and function based on the knowledge of gene products. Determination of gene expression-anatomy associations is crucial for this understanding. To elicit the association in the three-dimensional (3D) space, we introduce a novel technique for comprehensive mapping of endogenous gene expression into a web-accessible standard space: Transcriptome Tomography. The technique is based on conjugation of sequential tissue-block sectioning, all fractions of which are used for molecular measurements of gene expression densities, and the block- face imaging, which are used for 3D reconstruction of the fractions. To generate a 3D map, tissues are serially sectioned in each of three orthogonal planes and the expression density data are mapped using a tomographic technique. This rapid and unbiased mapping technique using a relatively small number of original data points allows researchers to create their own expression maps in the broad anatomical context of the space. In the first instance we generated a dataset of 36,000 maps, reconstructed from data of 61 fractions measured with microarray, covering the whole mouse brain (ViBrism: http://vibrism.riken.jp/3dviewer/ex/index.html) in one month. After computational estimation of the mapping accuracy we validated the dataset against existing data with respect to the expression location and density. To demonstrate the relevance of the framework, we showed disease related expression of Huntington's disease gene and Bdnf. Our tomographic approach is applicable to analysis of any biological molecules derived from frozen tissues, organs and whole embryos, and the maps are spatially isotropic and well suited to the analysis in the standard space (e.g. Waxholm Space for brain-atlas databases). This will facilitate research creating and using open-standards for a molecular-based understanding of complex structures; and will contribute to new insights into a broad range of biological and medical questions.

    DOI: 10.1371/journal.pone.0045373

    Web of Science

    PubMed

  23. Interactive Registration of Intracellular Volumes with Radial Basis Functions. Reviewed

    Shin Yoshizawa 0001, Satoko Takemoto, Miwa Takahashi, Makoto Muroi, Sayaka Kazami, Hiromi Miyoshi, Hideo Yokota

    Int. J. Comput. Intell. Appl.   Vol. 9 ( 3 ) page: 207 - 224   2010

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    Language:English   Publishing type:Research paper (scientific journal)  

    We propose a novel approach to 3D image registration of intracellular volumes. The approach extends a standard image registration framework to the curved cell geometry. An intracellular volume is mapped onto another intracellular domain by using two pairs of point set surfaces approximating their nuclear and plasma membranes. The mapping function consists of the affine transformation, tetrahedral barycentric interpolation, and least-squares formulation of radial basis functions for extracted cell geometry features. An interactive volume registration system is also developed based on our approach. We demonstrate that our approach is capable of creating cell models containing multiple organelles from observed data of living cells. © 2010 Imperial College Press.

    DOI: 10.1142/S1469026810002847

    Scopus

  24. Multi-dimensional intracelluar image processing

    Yokota Hideo, Yoshizawa Shin, Takemoto Satoko, Nishimura Masaomi, Makinouchi Akitake

    Proceedings of JSPE Semestrial Meeting   Vol. 2010 ( 0 ) page: 659 - 660   2010

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)   Publisher:The Japan Society for Precision Engineering  

    DOI: 10.11522/pscjspe.2010S.0.659.0

    J-GLOBAL

  25. Performance Evaluation of Image Segmentation for Intracellular Image

    Takemoto Satoko, Yokota Hideo, Makinouchi Akitake

    Proceedings of JSPE Semestrial Meeting   Vol. 2010 ( 0 ) page: 665 - 666   2010

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    Publishing type:Research paper (conference, symposium, etc.)   Publisher:The Japan Society for Precision Engineering  

    A novel segmentation framework, which has a generality enough to be used for a variety of intracellular image segmentation tasks, has been proposed. With this framework, an optimal algorithm suited to each segmentation task can be selected automatically. To select the correct algorithm, we have proposed two evaluation criteria derived from region similarity based on intensity-based features and boundary shape-based features. Furthermore, using our framework, we can rank different algorithms, as well as define each algorithm&prime;s parameters. We tested our prototype framework on confocal microscope images, and application of these criteria gave highly accurate segmentation results without missing any biologically important image characteristics.

    DOI: 10.11522/pscjspe.2010S.0.665.0

  26. Large-Scale Parallel Analysis of Image Features for Intracellular Image Segmentation

    Takemoto Satoko, Yoshizawa Shin, Yokota Hideo

    Proceedings of JSPE Semestrial Meeting   Vol. 2010 ( 0 ) page: 433 - 434   2010

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)   Publisher:The Japan Society for Precision Engineering  

    DOI: 10.11522/pscjspe.2010A.0.433.0

    J-GLOBAL

  27. Registration of Large Scale Intracellular 3D Image Data

    Yoshizawa Shin, Takemoto Satoko, Takahashi Miwa, Muroi Makoto, Kazami Sayaka, Miyoshi Hiromi, Yokota Hideo

    Proceedings of JSPE Semestrial Meeting   Vol. 2010 ( 0 ) page: 79 - 80   2010

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)   Publisher:The Japan Society for Precision Engineering  

    Modern science and engineering have been based on real-world images. In particular, intracellular image analysis become the mainstream in popular life science because of recent advances in confocal laser scanning microscopy and fluorescent observation technologies. Unfortunately, a number of observable matters simultaneously is limited. Therefore, image registration is necessary in order to integrate separately observed images for analyzing correlation and generating simulation shape models. However, intracellular images usually consist of millions to billions voxels. Hence efficient methods are required for such registration tasks. In this talk, we propose an efficient intracellular image registration method. The mapping between two images is constructed by using the cell&prime;s geometric features and its radial basis function fitting. We achieved interactive registration rate by approximating the plasma and nuclear membranes with point set surfaces.

    DOI: 10.11522/pscjspe.2010A.0.79.0

    J-GLOBAL

  28. Algorithm Selection for Intracellular Image Segmentation Based on Region Similarity. Reviewed

    Satoko Takemoto, Hideo Yokota

    2009 9TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS     page: 1413 - 1418   2009

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    This paper deals with the problem of intracellular image segmentation. Our goal is to propose an algorithm selection framework that has the potential to be general enough to be used for a variety of intracellular image segmentation tasks. With this framework, an optimal algorithm suited to each segmentation task can be selected automatically by our proposed evaluation criteria derived from region similarity of image features and boundary shape. Furthermore, using our framework, we can rank different algorithms, as well as define each algorithm's parameters. We tested our prototype framework on confocal microscope images and showed that application of these criteria gave highly accurate segmentation results without missing any biologically important image characteristics.

    DOI: 10.1109/ISDA.2009.205

    Web of Science

    Other Link: https://dblp.uni-trier.de/db/conf/isda/isda2009.html#TakemotoY09

  29. Intracellular Volume Registration. Reviewed

    Shin Yoshizawa 0001, Satoko Takemoto, Miwa Takahashi, Makoto Muroi, Sayaka Kazami, Hiromi Miyoshi, Hideo Yokota

    2009 9TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS     page: 1407 - 1412   2009

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    The paper proposes a novel 3D image registration approach to calculating intracellular volumes. The approach extends a standard image registration framework to the curved cell geometry. An intracellular volume is mapped onto another intracellular domain by using two pairs of point set surfaces approximating their nuclear and plasma membranes. The approach is implemented to an interactive volume registration system. We demonstrate that our approach can create models of cells with multiple organelles from data collected from living cells.

    DOI: 10.1109/ISDA.2009.42

    Web of Science

    Other Link: https://dblp.uni-trier.de/db/conf/isda/isda2009.html#YoshizawaTTMKMY09

  30. Segmentation of Anatomical Structure by Using a Local Classifier Derived from Neighborhood Information Reviewed

    Satoko Takemoto, Hideo Yokota, Ryutaro Himeno, Taketoshi Mishima

    2008 CONFERENCE ON HUMAN SYSTEM INTERACTIONS, VOLS 1 AND 2     page: 732 - 736   2008

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    Rapid advances in imaging modalities have increased the importance of image segmentation techniques. These techniques automatically extract data for the anatomical structure of interest and facilitate their quantitative analysis. Here we present a framework for a semi-automatic segmentation method that incorporates a local classifier derived from a neighboring image. Using the local classifier we were able to consider otherwise challenging cases of segmentation merely as two-class classification without any complicated parameters. Our method is simple to implement and easy to operate. We successfully tested our method on computed tomography images.

    DOI: 10.1109/HSI.2008.4581531

    Web of Science

  31. Observation of ovarian internal structures during the estrous cycle of Mare. Reviewed

    Hirano Y, Kimura J, Nambo Y, Yokota H, Nakamura S, Himeno R, Takemoto S, Mishima T, Matsui M, Miyake Y-I

    Animal reproduction science   Vol. 94   page: 210 - 214   2006

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  32. Semi-automated Color Segmentation from a Biological Cross-sectional Image Series : Follicle Segmentation for Visualization of the Equine Ovary

    TAKEMOTO Satoko, HIRANO Yuko, YOKOTA Hideo, NAKAMURA Sakiko, KIMURA Junpei, NAMBO Yasuo, TSUMAGARI Shigehisa, HIMENO Ryutaro, MISHIMA Taketoshi

    The Journal of the Institute of Image Electronics Engineers of Japan   Vol. 34 ( 6 ) page: 770 - 777   2005.11

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    This paper proposes a semi-automatic segmentation method for the 3D-ISM system which enables the capture of a high-resolution full-color cross-sectional image series of biological sample. Our approach is based on region-based segmentation and an adaptive classification technique by using the <i>Otsu</i> method, so it can be applied to an object like biological tissue which has different features by location. As a result, we have achieved to develop the method to decrease the degree of manual operation required. This paper also shows experimental results of applying our method to visualize the internal structure of the equine ovary. We have confirmed the spatial arrangement inside the ovary which had not been revealed so far.

    DOI: 10.11371/iieej.34.770

  33. Semi-automated color segmentation from a biological cross-sectional image series: follicle segmentation from the equine ovary. Reviewed

    Satoko Takemoto, Taketoshi Mishima, Ryutaro Himeno, Junpei Kimura, Shigehisa Tsumagari, Hideo Yokota, Sakiko Nakamura, Yasuo Nambo

    2004 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN & CYBERNETICS, VOLS 1-7     page: 3076 - 3081   2004

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    This paper proposes a semi-automatic segmentation method for the 3D-ISM system which enables the capture of a high-resolution full-color cross-sectional image series of a biological sample. Our approach is based on region-based segmentation and an adaptive classification technique by using the Otsu method, so it can be applied to an object like biological tissue which has different colors by location. As a result, we have achieved to develop the method to decrease the degree of manual operation required. This paper also shows experimental results of applying our method to visualize the internal structure of the equine ovary. We have confirmed the spatial arrangement inside the ovary which had not been revealed so far.

    DOI: 10.1109/ICSMC.2004.1400811

    Web of Science

    Other Link: https://dblp.uni-trier.de/db/conf/smc/smc2004-4.html#TakemotoMHKTYNHN04

▼display all

MISC 56

  1. 機械学習を用いた内視鏡画像に対する早期胃がん領域の自動認識

    横田秀夫, 竹本智子, 堀圭介, 坂井良匡, 池松弘朗, 矢野友規

    日本胃癌学会総会記事   Vol. 92nd   2020

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    J-GLOBAL

  2. 高効率なAIスキームを用いた,少数例の学習画像による早期胃がんの領域自動検出モデルの構築

    堀圭介, 竹本智子, 横田秀夫

    Gastroenterological Endoscopy (Web)   Vol. 62 ( Supplement1 )   2020

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  3. 高効率な学習モデルと日常診療アノテーションデータによる,内視鏡的自動診断AI生成の試み

    堀圭介, 竹本智子, 横田秀夫, 松崎博貴, 竹下修由, 稲場淳, 山本陽一, 門田智裕, 中條恵一郎, 村野竜朗, 新村健介, 依田雄介, 池松弘明, 矢野友規

    日本胃癌学会総会記事   Vol. 92nd   2020

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    J-GLOBAL

  4. Convolutional Neural Networkによる内視鏡画像からの早期胃がんの自動検出

    竹本智子, 堀圭介, 坂井良匡, 坂井良匡, 西村将臣, 池松弘朗, 矢野友規, 横田秀夫

    光量子工学研究 第6回 理研シンポジウム 平成30年     2018

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  5. 深層学習による内視鏡画像での早期胃がん検出

    坂井良匡, 坂井良匡, 竹本智子, 堀圭介, 西村将臣, 池松弘朗, 矢野友規, 横田秀夫

    光量子工学研究 第6回 理研シンポジウム 平成30年     2018

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  6. マウスの脳の二光子顕微鏡画像からの神経細胞認識処理の開発

    君塚涼, 道川貴章, 竹本智子, 横田秀夫, 宮脇敦史, 清水昭伸

    日本医用画像工学会大会予稿集(CD-ROM)   Vol. 37th   2018

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  7. インスリン受容体近傍の局所的な膜動態の観察

    梅林美和, REYMOND Luc, 竹本智子, 横田秀夫, JOHNSSON Kai, REIZMAN Howard

    脂質生化学研究   Vol. 60   page: 159‐161 - 161   2018

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    多様な脂質で構成される生体膜の脂質分布は不均一で、ある機能蛋白質と特定の集合他が存在するとされる。近年の超解像顕微鏡法により、ある脂質と特定の膜蛋白質の会合体の存在が示されている。しかし、それらは特定の蛋白質や脂質の別個の観察による間接的なもので、特定の膜蛋白質の動態とその近傍の微小膜環境を同時、且つ直接的な観察法は確立していない。そこで、私達は生細胞における特定の膜蛋白質とその周辺の局所的な膜環境を同時に、且つ直接的に観察する技術の必要性を感じ、その開発を進めた。私達は、細胞膜上のインスリン受容体と環境感受性プローブのNile redを、リンカーを介して連結することで、インスリン受容体近傍の微小膜領域の可視化に成功した。この方法では、Nile redは受容体近傍のみに局在するため、従来型の顕微鏡下でもインスリン受容体周辺の微小膜領域の観察が可能となる。開発した技術を用いて、インスリン刺激時におけるインスリン受容体近傍の微小膜環境を観察したところ、受容体近傍の微小膜領域は刺激時に極性が高くなることが示された。一方、細胞膜の広域的な膜環境やGPIアンカー蛋白質のCD59近傍の微小膜領域ではインスリン刺激による明確な変化は見られなかった。この結果は、インスリン刺激により、インスリン受容体近傍の微小膜領域が大きく変化しており、広域の細胞膜とは異なる動態を持つことを示唆する。(著者抄録)

    J-GLOBAL

  8. OCT画像から網膜内の層厚を検出するロバストなエッジ検出 2

    工藤重樹, 竹本智子, 横田秀夫, 秋葉正博

    光量子工学研究 第5回 理研シンポジウム 平成29年     page: 151‐152   2017

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    J-GLOBAL

  9. 画像処理法の決定支援システムSommelierによる細胞膜認識手順の自動化

    竹本智子, 梅林美和, 森田正彦, RIEZMAN Howard, 横田秀夫

    光量子工学研究 第5回 理研シンポジウム 平成29年     page: 121‐122   2017

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    J-GLOBAL

  10. Preliminary study on extraction of cell bodies from a three dimensional brain histological image Reviewed

    伊藤達也, 斉藤篤, 横田秀夫, 竹本智子, 辻村有紀, 宮脇敦史, 清水昭伸

    電子情報通信学会技術研究報告   Vol. 115 ( 401(MI2015 73-145) ) page: 283‐288   2016

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  11. 核膜サブドメインPore‐free islandは核膜孔形成によって偏縁から消失する

    三村恭弘, 竹本智子, 横田秀夫, 今本尚子

    日本細胞生物学会大会(Web)   Vol. 68th   page: ROMBUNNO.P2‐6 (WEB ONLY) - 87   2016

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    Language:Japanese   Publishing type:Research paper, summary (national, other academic conference)   Publisher:(一社)日本細胞生物学会  

    J-GLOBAL

  12. バイオイメージ解析のための画像処理法の決定支援システムの開発

    竹本智子, 横田秀夫

    光量子工学研究-若手・中堅研究者から見た光量子工学の展開 第4回 理研シンポジウム 平成28年     page: 51   2016

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    J-GLOBAL

  13. OCT画像から網膜内の層厚を検出するためのロバストなエッジ検出 アルゴリズムの開発 その後の進展

    工藤重樹, 竹本智子, 横田秀夫, 秋葉正博

    光量子工学研究-若手・中堅研究者から見た光量子工学の展開 第4回 理研シンポジウム 平成28年     page: 59‐60   2016

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    J-GLOBAL

  14. 間期の核膜孔複合体形成と核膜サブドメインPore‐free islandの消失

    三村恭弘, 竹本智子, 横田秀夫, 今本尚子

    日本分子生物学会年会プログラム・要旨集(Web)   Vol. 39th   page: ROMBUNNO.1PS12‐4 (WEB ONLY)   2016

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  15. トランスクリプトーム トモグラフィー:遺伝子発現を脳3次元空間にマップする

    於保祐子, 於保祐子, 中村佐紀子, 辻村有紀, 西村将臣, 竹本智子, 森田正彦, 俵丈展, 横田秀夫

    3次元内部構造顕微鏡による3次元計測の生物・材料分野への挑戦と展開 理研シンポジウム 平成27年     page: 15 - 17   2015

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  16. 迅速な生物画像解析を支援する画像処理法の性能評価システム

    竹本智子, 高橋美和, 横田秀夫

    光量子工学研究 第3回 理研シンポジウム 平成27年     page: 171‐172   2015

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  17. ViBrism‐DBデータセットを用いた遺伝子発現地図と共発現ネットワークの統合解析で明らかになった発生学的に保存された脳の意匠

    於保祐子, 下川和郎, 竹本智子, 横田秀夫

    日本分子生物学会年会プログラム・要旨集(Web)   Vol. 36th   page: 3P-0578 (WEB ONLY)   2013

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    J-GLOBAL

  18. 細胞内画像処理に向けた画像処理統合システムVCAT5の開発

    横田秀夫, 吉澤信, 西村将臣, 竹本智子, 井尻敬, 森田正彦, 尾崎弘武, 牧野内昭武

    日本医用画像工学会大会予稿集(CD-ROM)   Vol. 32nd ( Suppl. ) page: ROMBUNNO.OP7-4 - 3   2013

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    Language:Japanese   Publishing type:Research paper, summary (national, other academic conference)   Publisher:日本医用画像工学会  

    近年のバイオイメージング技術の進展に伴い、顕微鏡による細胞観察画像は、時系列変化を含む3次元原情報となってきた。これらの膨大な細胞画像を定量解析する技術が現在求められている。我々のグループでは、ImageJに変わる多次元細胞画像に体する画像処理プラットフォームとしてVCAT5を開発してきた。このシステムは、プラグインの形式にて新しい処理を容易に追加可能なインターフェースを有し、各種フィルタ、多次元の特徴空間、SVMやPCAなどの判別手法を組み合わせてユーザーが新しい処理アルゴリズムを構築することも可能である。さらに、領域抽出法やボリュームレンダリングやサーフェスレンダリングによる可視化技術を搭載している。現在までに100種類のプラグインを開発し、アカデミアに向けて無償にて公開を開始した。本講演ではこのシステムについて紹介すると共に、実際に細胞画像の処理例を報告する。(著者抄録)

    J-GLOBAL

  19. 細胞観察画像の領域分割法選択のための性能評価システムの開発

    竹本智子, 吉澤信, 横田秀夫

    光量子工学研究 第1回 理研シンポジウム 平成25年     page: 75   2013

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    J-GLOBAL

  20. バイオイメージデータから定量解析・シミュレーションのための画像解析ソフトウエアVCAT5の開発

    横田秀夫, 西村将臣, 竹本智子, 吉澤信, 辻村有紀

    バイオイメージング   Vol. 21 ( 2 ) page: 212 - 213   2012

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    Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (scientific journal)   Publisher:日本バイオイメージング学会  

    DOI: 10.15004/00000538

    J-GLOBAL

  21. 新規の核膜孔複合体は既存の核膜孔複合体の近傍に形成される

    三村恭弘, 竹本智子, 横田秀夫, 今本尚子

    日本分子生物学会年会プログラム・要旨集(Web)   Vol. 35th   page: 4P-0101 (WEB ONLY)   2012

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  22. 細胞内観察画像における領域分割性能の評価

    竹本智子, 横田秀夫

    VCADシステム研究2010 VCADの未来 理研シンポジウム 平成23年     page: 228 - 231   2011

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  23. VCADシステム研究2009―ものつくりとバイオ研究分野における計測・モデリング・シミュレーション―細胞内画像のための領域抽出アルゴリズムの評価システム

    竹本智子, 横田秀夫

    VCADシステム研究2009 ものつくりとバイオ研究分野における計測・モデリング・シミュレーション 理研シンポジウム 平成22年     page: 123   2010

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  24. 生体力学シミュレーション研究 新しい生体3D情報計測法:全発現遺伝子CT

    於保祐子, 中村佐紀子, 竹本智子, 西村将臣, 辻村有紀, 姫野龍太郎, 横田秀夫

    生体力学シミュレーション研究 理研シンポジウム 平成22年     page: 35 - 37   2010

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  25. 定量的3次元遺伝子発現データに基づいたマウス脳アトラスの作成とその解析

    於保祐子, 竹本智子, 横田秀夫

    生化学   Vol. 83回・33回   page: ROMBUNNO.1P-0873 - 0873   2010

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  26. 細胞内画像処理のすすめ

    横田秀夫, 吉澤信, 竹本智子, 西村将臣, 牧野内昭武

    ViEWビジョン技術の実利用ワークショップ講演論文集(CD-ROM)   Vol. 2010   page: ROMBUNNO.B-1K   2010

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  27. Predicting Segmentation Quality for Intracellular Images

    竹本智子, 横田秀夫, 吉森保, 牧野内昭武

    ViEWビジョン技術の実利用ワークショップ講演論文集(CD-ROM)   Vol. 2010   page: ROMBUNNO.I-48   2010

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  28. Population of Follicles and Luteal Structures during the Oestrous Cycle of Mares Detected by Three-Dimensional Internal Structure Microscopy Reviewed

    Y. Hirano, J. Kimura, Y. Nambo, H. Yokota, S. Nakamura, S. Takemoto, R. Himeno, T. Mishima, M. Matsui, Y. -I. Miyake

    ANATOMIA HISTOLOGIA EMBRYOLOGIA   Vol. 38 ( 3 ) page: 214 - 218   2009.6

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    The structure of the equine ovary is different from that of other mammals in its extremely large size, the presence of ovarian fossa and the inverted location of its cortex and medulla. A three-dimensional internal structure microscopy (3D-ISM), which consists of a computer-controlled slicer, a CCD camera, a laser disc recorder and a PC, is very useful for the observation of the internal structures in equine ovaries. In addition, the three-dimensional images of follicles and corpus luteum (CL) reconstructed by the segmentation technique can clarify the spatial arrangement in the equine ovary. In this study, to understand the changes in the ovarian internal structures of the mare during the oestrous cycle, the size and numbers of follicles and luteal structures were analysed by 3D-ISM in addition to the concentrations of progesterone (P(4)) and oestradiol-17 beta. As a result, many small follicles (&lt; 10 mm in diameter) were detected. It was recognized that the luteal structures were distinguished into three types, such as the corpus haemorragicum (CH), which is formed by blood elements at the cavity after ovulation, CL and corpus albican (CA). There were some CHs and CL in the group, which had the concentration of P(4) &gt; 1 ng/ml. CHs were also observed in the group, which had low level of P(4) (P(4) &lt; 1 ng/ml). CAs were found regardless of the P(4) level. In conclusion, 3D-ISM enabled the internal observation of the ovarian structures in detail, and estimation of the stage of the ovarian cycle with complementary physiological information. The findings by 3D-ISM provide basic information for clinical applications.

    DOI: 10.1111/j.1439-0264.2008.00924.x

    Web of Science

    Scopus

    PubMed

  29. Segmentation of Anatomical Structure by Using a Local Classifier Derived from Neighborhood Information Reviewed

    S. Takemoto, H. Yokota, T. Mishima, R. Himeno

    HUMAN-COMPUTER SYSTEMS INTERACTION: BACKGROUNDS AND APPLICATIONS   Vol. 60   page: 171 - +   2009

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    Language:English   Publishing type:Article, review, commentary, editorial, etc. (international conference proceedings)   Publisher:SPRINGER-VERLAG BERLIN  

    Rapid advances in imaging modalities have increased the importance of image segmentation techniques. Image segmentation is a process that divides an image into regions based on the image's internal components to distinguish between the component of interest and other components. We use this process to analyze the region of the component of interest and acquire more detailed quantitative data about the component. However, almost all processes of segmentation of anatomical structures have inherent problems such as the presence of image artifacts and the need for complex parameter settings. Here, we present a framework for a semi-automatic segmentation technique that incorporates a local classifier derived from a neighboring image. By using the local classifier, we were able to consider otherwise challenging cases of segmentation merely as two-class classifications without any complicated parameters. Our method is simple to implement and easy to operate. We successfully tested the method on computed tomography images.

    Web of Science

    Scopus

  30. 生物の定量解析,数値シミュレーションに向けたディジタル解析システムの開発

    横田秀夫, 吉澤信, 竹本智子, 西村将臣, 牧野内昭武

    日本分子生物学会年会講演要旨集   Vol. 32nd ( Vol.3 ) page: 36   2009

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  31. 出生後12ヵ月間におけるウマ卵巣構造の観察 実質帯と血管帯の体積変化について

    阿久澤 洋貴, 平野 悠子, 竹本 智子, 木村 順平, 南保 泰雄, 大滝 忠利, 中村 佐紀子, 横田 秀夫, 姫野 龍太郎, 樋口 徹, 荒木 成就, 津曲 茂久

    日本獣医学会学術集会講演要旨集   Vol. 146回   page: 231 - 231   2008.9

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  32. VCADシステム研究2008―ものつくりから細胞まで―領域抽出:画像特徴と形状の評価によるオブジェクト抽出

    竹本智子, 横田秀夫

    VCADシステム研究2008 ものつくりから細胞まで 理研シンポジウム 平成20年     page: 139 - 140   2008

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  33. 生体形状情報の数値化及びデータベース構築研究 脳内における遺伝子発現の3次元空間解析

    於保祐子, 中村佐紀子, 竹本智子, 横田秀夫, 姫野龍太郎

    生体形状情報の数値化及びデータベース構築研究 理研シンポジウム 平成20年     page: 105 - 111   2008

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  34. ライブセルイメージの領域抽出とVCADツールによる可視化

    竹本智子, 横田秀夫

    VCADシステム研究 ものつくりから生きた細胞まで、現物を扱うための基盤技術を創る 理研シンポジウム 平成19年     page: 220   2007

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  35. ウマ卵巣の3次元内部構造顕微鏡による観察(続報)

    木村順平, 平野悠子, 竹本智子, 中村佐紀子, 姫野龍太郎, 三島健稔, 南保泰雄, 横田秀夫

    日本獣医学会学術集会講演要旨集   Vol. 142nd   page: 35 - 35   2006.8

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  36. 生体ボリュームデータに対する特定領域の自動抽出法

    竹本智子, 横田秀夫, 島井博行, 本多英晴, 中島佳奈子, 姫野龍太郎, 三島健稔

    生体形状情報の数値化及びデータベース構築研究 理研シンポジウム 平成18年11月8日     page: 52 - 64   2006

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  37. Digitization and database construction research of organism shape information.The observation of the mouse ovarium internal construction using the three-dimensional internal construction microscope equipment ( 3D - ISM ).

    木村順平, 平野悠子, 猪飼志保, 竹本智子, 中村佐紀子, 横田秀夫, 姫野龍太郎, 三島健稔, 南保泰雄, 津曲茂久, 松井基純, 三宅陽一

    生体形状情報の数値化及びデータベース構築研究 理研シンポジウム 平成18年     page: 126-135,XV-XVII   2006

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  38. Digitization and database construction research of organism shape information. The examination of the automatic organization extraction method from the full color organism connected cross section image. The third report. Region extraction of the horse ova

    竹本智子, 横田秀夫, 平野悠子, 中村佐紀子, 木村順平, 南保泰雄, 津曲茂久, 三宅陽一, 姫野龍太郎, 三島健稔

    生体形状情報の数値化及びデータベース構築研究 理研シンポジウム 平成18年     page: 54-63,V   2006

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  39. Three-dimensional reconstruction of the equine ovary Reviewed

    J Kimura, Y Hirano, S Takemoto, Y Nambo, T Ishinazaka, R Himeno, T Mishima, S Tsumagari, H Yokota

    ANATOMIA HISTOLOGIA EMBRYOLOGIA-JOURNAL OF VETERINARY MEDICINE SERIES C   Vol. 34 ( 1 ) page: 48 - 51   2005.2

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    The equine ovary has a very unique structure in terms of its extreme large size, the presence of the ovulation fossa and the inverted location of its cortex and medulla. In the previous study, it was recognized that the application of three-dimensional internal structure microscopy (3D-ISM) to observe the mare ovary is very effective. Three-dimensional reconstruction of serially sliced images made by 3D-ISM was successful in this study with the aid of the sophisticated image processing technique. The rotation of the reconstructed ovary has been carried out with and without the application of the transparency technique in the ovarian stromal region. The spatial localization of follicles and corpus luteum was clearly visualized by rotating the reconstructed image of the ovary. The extraction of the images of follicles and corpus luteum was also available and gave a quantifiable understanding of their structure.

    DOI: 10.1111/j.1439-0264.2004.00567.x

    Web of Science

    Scopus

    PubMed

  40. 3次元内部構造顕微鏡装置(3D‐ISM)を用いたウマ卵巣の観察―妊娠馬における卵巣の内部構造について―

    猪飼志保, 平野悠子, 木村順平, 石名坂豪, 横田秀夫, 中村佐紀子, 姫野龍太郎, 松井基純, 三宅陽一, 仙波裕之, 竹本智子, 三島健稔, 南保泰雄, 津曲茂久

    日本獣医学会学術集会講演要旨集   Vol. 139th   page: 192 - 192   2005

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  41. 三次元内部構造顕微鏡装置を用いたウマ卵巣の観察~妊娠期におけるウマ卵巣の内部構造について~

    猪飼志保, 平野悠子, 木村順平, 石名坂豪, 横田秀夫, 中村佐紀子, 姫野龍太郎, 松井基純, 三宅陽一, 樋口徹, 竹本智子, 三島健稔, 南保泰雄, 津曲茂久

    日本獣医学会学術集会講演要旨集   Vol. 140th   page: 156 - 156   2005

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  42. 三次元内部構造顕微鏡装置(3D‐ISM)を用いたウマ卵巣の観察~0歳齢における卵巣内部構造の変化~

    平野悠子, 松井基純, 横田秀夫, 中村佐紀子, 姫野龍太郎, 竹本智子, 三島健稔, 樋口徹, 南保泰雄, 木村順平, 三宅陽一

    日本獣医学会学術集会講演要旨集   Vol. 140th   page: 156 - 156   2005

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  43. Examination of automatic organization extraction method from full color organism continuous cross section images - trial visualization inside horse ovarium -.

    竹本智子, 横田秀夫, 平野悠子, 中村佐紀子, 木村順平, 南保泰雄, 津曲茂久, 三宅陽一, 姫野龍太郎

    生体形状情報の数値化及びデータベース構築研究 理研シンポジウム 平成17年     page: 45-55,XII   2005

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  44. Examination of extraction method from full color conitnuous organism cross section images using color histogram.

    本多英晴, 竹本智子, 横田秀夫, 覚正信徳, 姫野龍太郎, 三島健稔, 大竹政光

    生体形状情報の数値化及びデータベース構築研究 理研シンポジウム 平成17年     page: 56-70,XIII-XVI   2005

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  45. The observation of mare ovaries during pregnancy by three-dimensional internal structure microscopy (3D-ISM).

    Y Hirano, M Matsui, S Ikai, J Kimura, T Ishinazaka, S Tsumagari, H Yokota, S Nakamura, S Takemoto, T Mishima, Y Nambo, YI Miyake

    BIOLOGY OF REPRODUCTION     page: 121 - 121   2005

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    Language:English   Publishing type:Research paper, summary (international conference)   Publisher:SOC STUDY REPRODUCTION  

    Web of Science

  46. 三次元内部構造顕微鏡装置(3D-ISM)を用いたウマ卵巣の観察 卵巣内構造物の三次元化および空間的位置関係の検索

    平野 悠子, 木村 順平, 猪飼 志保, 石名坂 豪, 津曲 茂久, 横田 秀夫, 中村 佐紀子, 姫野 龍太郎, 竹本 智子, 三島 健稔, 本多 英晴, 大竹 政光, 南保 泰雄, 松井 基純, 三宅 陽一

    The Journal of Reproduction and Development   Vol. 50 ( Suppl. ) page: j83 - j83   2004.8

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  47. Visualization for the Follicle Anatomy in the Mare Ovary : Investigation into Specific Structure of the Ovary in the Perissodactyl

    TAKEMOTO Satoko, YOKOTA Hideo, HIRANO Yuko, NAKAMURA Sakiko, KIMURA Junpei, NAMBO Yasuo, TSUMAGARI Sigehisa, HIMENO Ryutaro, MISHIMA Taketoshi

    形の科学会誌 = Bulletin of the Society for Science on Form   Vol. 19 ( 1 ) page: 101 - 102   2004.7

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  48. Automatic Tissue Segmentation from the Full-color Biological Images : The Trials of Follicle Segmentation from Mare Ovary using the Statistical Method Reviewed

    TAKEMOTO Satoko, YOKOTA Hideo, HIRANO Yuko, NAKAMURA Sakiko, KIMURA Junpei, NAMBO Yasuo, TSUMAGARI Sigehisa, HIMENO Ryutaro, MISHIMA Taketoshi

    IEICE technical report.   Vol. 103 ( 597 ) page: 37 - 42   2004.1

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    Language:Japanese   Publishing type:Research paper, summary (national, other academic conference)   Publisher:The Institute of Electronics, Information and Communication Engineers  

    The new observation system called 3D-ISM has been developed in recent years. This system allows filming the in-vivo fall-color images. These images will achieve the desired results in visualization of in-vivo structure that keeps the color information. For that purposes, we need the segmentation technique for the in-vivo color images. In this paper, we address the theme of follicle segmentation from mare ovary, using the statistical method called LSTMS for analyzing data. As a result, we achieved the visualization of all the follicles.

  49. 3次元内部構造顕微鏡を用いた生物構造情報を対象としたフェノタイプの数値化の試み

    横田秀夫, 覚正信徳, 中村佐紀子, 竹本智子, 本多英晴, 小林大祐, 三島健稔, 大竹政光, 姫野龍太郎

    日本分子生物学会年会プログラム・講演要旨集   Vol. 27th   page: 347   2004

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  50. Research on the automatic extraction method of tissue from the organism full color serial section image.

    竹本智子, 横田秀夫, 姫野龍太郎, 牧野内昭武, 三島健稔

    生体力学シミュレーション研究終了報告 理研シンポジウム 平成16年     page: 233 - 242   2004

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  51. カラーヒストグラムを利用したフルカラー連続生体断面画像からの抽出法の検討 Reviewed

    本多英晴, 竹本智子, 横田秀夫, 覚正信徳, 中村佐紀子, 姫野龍太郎, 三島健稔, 大竹政光

    電子情報通信学会大会講演論文集   Vol. 2004   page: 83   2004

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  52. Examination of automatic extraction of the chracteristic positions from the full color living body cross-section images.

    竹本智子, 横田秀夫, 三島健稔, 姫野龍太郎, 牧野内昭武

    生体力学シミュレーション研究 理研シンポジウム 平成15年     page: 100 - 106   2003

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  53. 生体内可視化のためのカラー断層画像列からの双方向セグメンテーション

    竹本智子, 横田秀夫, 姫野龍太郎, 牧野内昭武, 三島健稔

    日本医用画像工学会大会予稿集(CD-ROM)   Vol. 22nd   page: OP5-27   2003

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  54. 三次元内部構造顕微鏡装置を用いたウマ卵巣の観察―妊娠期のウマ卵巣の特徴について―

    平野悠子, 木村順平, 横田秀夫, 中村佐紀子, 竹本智子, 三島健稔, 牧野内昭武, 南保泰雄, 津曲茂久

    日本獣医学会学術集会講演要旨集   Vol. 136th   page: 193 - 193   2003

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  55. Automatic Extraction of the Interest Orgamization from Full-Color Continuous Image for Biological Sample : Report 1: Four-level selection of the interest area Reviewed

    TAKEMOTO Satoko, YOKOTA Hideo, SHIMAI Hiroyuki, MAKINOUCHI Akitake, MISHIMA Taketoshi

    Journal of the Visualization Society of Japan   Vol. 22   page: 489 - 492   2002.7

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    DOI: 10.3154/jvs.22.1Supplement_489

  56. Automatic region extraction from continuous cross section images, and generation of surface data.

    横田秀夫, 島井博行, 竹本智子, 平田忍, 覚正信徳, 中村佐紀子, 三島健稔, 牧野内昭武

    ものつくり情報技術統合化研究 第2回 理研シンポジウム 平成14年     page: 30 - 42   2002

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KAKENHI (Grants-in-Aid for Scientific Research) 6

  1. Development of AI-based diagnostic imaging method utilizing functional features for early gastric cancer

    Grant number:21K12742  2021.4 - 2024.3

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Authorship:Principal investigator 

    Grant amount:\4290000 ( Direct Cost: \3300000 、 Indirect Cost:\990000 )

  2. Time-lapse image analysis of the local membrane environment surrouding the insulin receptor with an information science approach

    Grant number:16K16153  2016.4 - 2020.3

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Young Scientists (B)

    Takemoto Satoko

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    Authorship:Principal investigator 

    Grant amount:\3900000 ( Direct Cost: \3000000 、 Indirect Cost:\900000 )

    In this study, in order to understand how the membrane domain surrounding signaling molecules changes during insulin signaling, we have developed an image analysis procedure. The procedure includes automatic detection for insulin receptor from noisy time-lapse images, measuring membrane fluidity based on Generalized polarization (GP) value, and visualization of GP value using Zero-mean normalized cross correlation (ZNCC).
    Our results reveals that the membrane fluidity of local environment surrounding the insulin receptor increased upon insulin stimulation. Furthermore, we found the local membrane environment of the insulin receptor was quite dynamic and heterogeneous. These results suggest that the insulin receptor has distinct local membrane environment from the general plasma membrane.

  3. Geomety and Topology of 3D Beef Marbling for Computational Food Science

    Grant number:16K15019  2016.4 - 2019.3

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Challenging Exploratory Research

    Yoshizawa Shin, Nakamura Sakiko

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    Authorship:Coinvestigator(s) 

    Quality evaluation of Wagyu (Japanese beef) is important in animal husbandry, zootechnical science, and food industry. Especially, quantitative and objective analysis of fat marbling has been demanded. In this research, we proposed 3D geometric and topological analysis of beef fat marbling. For a given real beef fresh meet, we developed an imaging framework, noise reduction filters, fat marbling segmentation and labeling methods, geometric and topological feature analysis programs. We believe that our research contributes to beginning of Computational Food Science by combining geometry and topology, animal husbandry, and biochemical analysis.

  4. Bio Image Processing

    Grant number:15H05954  2015.6 - 2020.3

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)

    yokota hideo

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    Authorship:Coinvestigator(s) 

    In this research, we have developed many useful imaging and image processing methods and systems for bio-images, and applied them to biology and medical application. In particular, our new computational methods include several fast image filters, a robust algorithm for principal component analysis, and several deep learning frameworks for medical image analysis. We have also developed a cloud-based image management platform (RBICP), an integrated image processing software (VCAT5) consisting of the proposed methods and other popular image processing techniques as plug-in programs, a performance evaluation system for image recognition (Sommelier), and a near infrared imaging system. Our systems have employed for various bio-image analysis. Furthermore, we held three algorithm contests using bio-images and contributed to integrating informatics and biology.

  5. Digital Image Analysis for Intracellular Logistics

    Grant number:20113007  2008 - 2012

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)

    MAKINOUCHI Akitake, TAKEMOTO Satoko, YOSHIZAWA Shin, NISHIMURA Masaomi, YOKOTA Hideo, SOGA Kohei

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    Recent advances in image acquisition technology on intracellular logistics demand new computational methods for quantitative analysis of intracellular images. In this research, we have proposed several new image processing algorithms and a long time-lapse imaging system in order to meet the demand. We have also developed a biologist-friendly software based on the proposed algorithms and made it available on the WWW without compensation.

  6. Development of the image segmentation system for intracellular organelles on living cell images

    Grant number:19800062  2007 - 2008

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Young Scientists (Start-up)

    TAKEMOTO Satoko

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    Authorship:Principal investigator 

    Grant amount:\3115000 ( Direct Cost: \2710000 、 Indirect Cost:\405000 )

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Industrial property rights 3

  1. 画像処理装置、画像処理方法およびプログラム

    竹本 智子, 横田 秀夫

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    Applicant:独立行政法人理化学研究所

    Application no:特願2009-110683  Date applied:2009.4

    Announcement no:特開2010-262350  Date announced:2010.11

    Patent/Registration no:特許第5284863号  Date issued:2013.6

    J-GLOBAL

  2. 中空臓器血管抽出方法、中空臓器血管抽出処理プログラムおよび画像処理装置

    横田 秀夫, 竹本 智子, 三島 健稔, 牧野内 昭武, 姫野 龍太郎

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    Applicant:独立行政法人理化学研究所

    Application no:特願2003-054799  Date applied:2003.2

    Announcement no:特開2004-261377  Date announced:2004.9

    Patent/Registration no:特許第4017157号  Date issued:2007.9

    J-GLOBAL

  3. 関心組織領域抽出方法、関心組織領域抽出プログラム及び画像処理装置

    横田 秀夫, 竹本 智子, 三島 健稔, 牧野内 昭武, 姫野 龍太郎

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    Applicant:独立行政法人理化学研究所

    Application no:特願2003-025277  Date applied:2003.1

    Announcement no:特開2004-234579  Date announced:2004.8

    Patent/Registration no:特許第4373682号  Date issued:2009.9

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Teaching Experience (Off-campus) 1

  1. バイオメディカルエンジニアリング

    北海道大学大学院)