Faculty Profiles - MORI, Kensaku

Papers - MORI, Kensaku

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Influence of using 3D images and 3D-printed objects on the formation of spatial mental models of experts and novices Invited Reviewed

MAEHIGASHI Akihiro, MIWA Kazuhisa, ODA Masahiro, NAKAMURA Yoshihiko, MORI Kensaku, IGAMI Tsuyoshi

JSAI Technical Report, SIG-ALST Vol. 79 ( 0 ) page： 08 2017.3

3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation Invited Reviewed

Oda, M; Shimizu, N; Roth, HR; Karasawa, K; Kitasaka, T; Misawa, K; Fujiwara, M; Rueckert, D; Mori, K

DEEP LEARNING IN MEDICAL IMAGE ANALYSIS AND MULTIMODAL LEARNING FOR CLINICAL DECISION SUPPORT Vol. 10553 page： 222 - 230 2017

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal) Publisher：Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

This paper presents a fully automated atlas-based pancreas segmentation method from CT volumes utilizing 3D fully convolutional network (FCN) feature-based pancreas localization. Segmentation of the pancreas is difficult because it has larger inter-patient spatial variations than other organs. Previous pancreas segmentation methods failed to deal with such variations. We propose a fully automated pancreas segmentation method that contains novel localization and segmentation. Since the pancreas neighbors many other organs, its position and size are strongly related to the positions of the surrounding organs. We estimate the position and the size of the pancreas (localization) from global features by regression forests. As global features, we use intensity differences and 3D FCN deep learned features, which include automatically extracted essential features for segmentation. We chose 3D FCN features from a trained 3D U-Net, which is trained to perform multi-organ segmentation. The global features include both the pancreas and surrounding organ information. After localization, a patient-specific probabilistic atlas-based pancreas segmentation is performed. In evaluation results with 146 CT volumes, we achieved 60.6% of the Jaccard index and 73.9% of the Dice overlap.

DOI： 10.1007/978-3-319-67558-9_26

Web of Science

Scopus

3Dプリンタ・ユーザーインターフェイス等の最新動向 Invited

森健策

インナービジョン Vol. 32 page： 44 - 45 2017

3D Printing for Medical Application Invited

MORI Kensaku

Medical Imaging and Information Sciences Vol. 34 ( 1 ) page： 1 - 6 2017

Authorship：Corresponding author Language：Japanese Publishing type：Research paper (scientific journal) Publisher：MEDICAL IMAGING AND INFORMATION SCIENCES

<p>This paper briefly introduces 3D printing technology for medical applications. 3D printing technology is obtaining a lot of attentions from various fields including rapid prototyping and manufacturing, home use and medical applications. Medical applications of 3D printing are including:（a）diagnostic aid,（b）surgical aid,（c）medical education,（d）medical training, and（e）re-generative medicine. In this short summary, we will briefly explain the various mechanism of 3D printing and several printing techniques for reproducing organ models by 3D printing techniques. Also the recent topics in international conferences are introduced here.</p>

DOI： 10.11318/mii.34.1

CiNii Research

3Dプリンタの医療応用 Invited

森健策

医用画像情報学会雑誌 Vol. 34 page： 1 - 6 2017

3Dプリンタ-の基礎と医療応用 Invited

森健策

月刊心臓 Vol. 49 page： 1104 - 1113 2017

Automatic Segmentation of Head Anatomical Structures from Sparsely-annotated Images Invited Reviewed

Sugino Takaaki, Roth Holger R., Eshghi Mohammad, Oda Masahiro, Chung Min Suk, Mori Kensaku

2017 IEEE INTERNATIONAL CONFERENCE ON CYBORG AND BIONIC SYSTEMS (CBS) page： 145 - 149 2017

Computer-Aided Diagnosis of Mammographic Masses Using Geometric Verification-Based Image Retrieval Invited Reviewed

Li Qingliang, Shi Weili, Yang Huamin, Zhang Huimao, Li Guoxin, Chen Tao, Mori Kensaku, Jiang Zhengang

MEDICAL IMAGING 2017: COMPUTER-AIDED DIAGNOSIS Vol. 10134 2017

Comparison of the Deep-Learning-Based Automated Segmentation Methods for the Head Sectioned Images of the Virtual Korean Human Project Invited Reviewed

Eshghi Mohammad, Roth Holger R., Oda Masahiro, Chung Min Suk, Mori Kensaku

PROCEEDINGS OF THE FIFTEENTH IAPR INTERNATIONAL CONFERENCE ON MACHINE VISION APPLICATIONS - MVA2017 page： 290 - 293 2017

A study on improvement of airway segmentation using Hybrid method Invited Reviewed

Qier M., Kitasaka T., Nimura Y., Oda M., Mori K.

Proceedings - 3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015 page： 549 - 553 2016.6

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal) Publisher：Proceedings - 3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015

This paper presents a method for extracting an airway region from 3D chest CT volumes that uses a combination of tube enhancement filters, voxel classification based on machine learning methods and graph-cut algorithm. Lots of previous methods utilize region growing or level set algorithms without any prior knowledge of bronchi, which always fail when they reach to the peripheral bronchi. In this paper, a method of extraction based on airway shape and machine learning is proposed. The proposed method detects candidate voxels of bronchial regions by using two types of enhancement filters, and a classifier model is built for selecting the proper candidates regions based on intensity and shape features and finally the selected candidate voxels are connected by graph-cut algorithm. We applied this method on six cases of 3D chest CT volumes. The results show that this method can extract the smaller airway branches without leaking into the lung parenchyma areas.

DOI： 10.1109/ACPR.2015.7486563

Scopus

Characterization of Colorectal Lesions Using a Computer-Aided Diagnostic System for Narrow-Band Imaging Endocytoscopy Invited Reviewed

Misawa Masashi, Kudo Shin-ei, Mori Yuichi, Nakamura Hiroki, Kataoka Shinichi, Maeda Yasuharu, Kudo Toyoki, Hayashi Takemasa, Wakamura Kunihiko, Miyachi Hideyuki, Katagiri Atsushi, Baba Toshiyuki, Ishida Fumio, Inoue Haruhiro, Nimura Yukitaka, Mori Kensaku

GASTROENTEROLOGY Vol. 150 ( 7 ) page： 1531 - + 2016.6

Influences of 3D images and 3D-printed objects on mental model construction of liver structure Invited Reviewed

MAEHIGASHI Akihiro, MIWA Kazuhisa, ODA Masahiro, NAKAMURA Yoshihiko, MORI Kensaku, IGAMI Tsuyoshi

JSAI Technical Report, SIG-ALST Vol. 76 ( 0 ) page： 14 2016.3

Authorship：Corresponding author Language：Japanese Publishing type：Research paper (scientific journal) Publisher：The Japanese Society for Artificial Intelligence

<p>In this study, we experimentally investigated the influence of a three-dimensional (3D) graphic image and a 3D-printed object on a spatial reasoning task in a situation where liver resection surgery was presupposed. The results of the study indicated that using a 3D-printed object produced more accurate and faster mental model construction of a liver structure than a 3D image. Using a 3D-printed object was assumed to reduce cognitive load and information accessing cost more than using a 3D image.</p>

DOI： 10.11517/jsaialst.76.0_14

CiNii Research

Cascade registration of micro CT volumes taken in multiple resolutions Invited Reviewed

Nagara K., Oda H., Nakamura S., Oda M., Homma H., Takabatake H., Mori M., Natori H., Rueckert D., Mori K.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9805 LNCS page： 269 - 280 2016

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal) Publisher：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

In this paper, we present a preliminary report of a multiscale registration method between micro-focus X-ray CT (micro CT) volumes taken in different scales. 3D fine structures of target objects can be observed on micro CT volumes, which are difficult to observe on clinical CT volumes. Micro CT scanners can scan specimens in various resolutions. In their high resolution volumes, ultra fine structures of specimens can be observed, while scanned areas are limited to very small. On the other hand, in low resolution volumes, large areas can be captured, while fine structures of specimens are difficult to observe. The fusion volume of the high and low resolution volumes will have benefits of both. Because the difference of resolutions between the high and low resolution volumes may vary greatly, an intermediate resolution volume is required for successful fusion of volumes. To perform such volume fusion, a cascade multi-resolution registration technique is required. To register micro CT volumes that have quite different resolutions, we employ a cascade co-registration technique. In the cascade co-registration process, intermediate resolution volumes are used in a registration process of the high and low resolution volumes. In the registration between two volumes, we apply two steps registration techniques. In the first step, a block division is used to register two resolution volumes. Afterward, we estimate the fine spatial positions relating the registered two volumes using the Powell method. The registration result can be used to generate a fusion volume of the high and low resolution volumes.

DOI： 10.1007/978-3-319-43775-0_24

Scopus

3Dプリンタ・ユーザーインターフェイス等の最新動向 Invited

森健策

インナービジョン Vol. - page： 44 - 45 2016

3Dプリンティングのハンドリングのノウハウ Invited

森健策

インナービジョン Vol. 31 page： 20 - 24 2016

Automated anatomical labeling of abdominal arteries and hepatic portal system extracted from abdominal CT volumes Invited Reviewed

Matsuzaki Tetsuro, Oda Masahiro, Kitasaka Takayuki, Hayashi Yuichiro, Misawa Kazunari, Mori Kensaku

MEDICAL IMAGE ANALYSIS Vol. 20 ( 1 ) page： 152 - 161 2015.2

Automated torso organ segmentation from 3D CT images using conditional random field Invited Reviewed

Yukitaka Nimura, Yuichiro Hayashi, Takayuki Kitasaka, Kazunari Misawa, and Kensaku Mori

Proceedings of SPIE Medical Imaging 2016 Vol. 9785 2015

3Dプリンティングの現状と将来展望:医用画像処理と3Dプリンタによる臓器実体モデル作成とその利用 Invited

森健策

光技術コンタクト Vol. 53 page： 20 - 27 2015

A study on improvement of airway segmentation using Hybrid method Invited Reviewed

Qier, M; Kitasaka, T; Nimura, Y; Oda, M; Mori, K

PROCEEDINGS 3RD IAPR ASIAN CONFERENCE ON PATTERN RECOGNITION ACPR 2015 page： 549 - 553 2015

Automated branching pattern report generation for laparoscopic surgery assistance Invited Reviewed

Oda Masahiro, Matsuzaki Tetsuro, Hayashi Yuichiro, Kitasaka Takayuki, Misawa Kazunari, Mori Kensaku

MEDICAL IMAGING 2015: COMPUTER-AIDED DIAGNOSIS Vol. 9414 2015

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Papers - MORI, Kensaku