Papers - MORI, Kensaku

ピットパターン特徴量の解析に向けた超拡大内視鏡画像の再構成法に関する初期的検討

伊東 隼人, 小田 昌宏, 森 悠一, 三澤 将史, 工藤 進英, 森 健策

第40回日本医用画像工学会大会予稿集     page： 309 - 317   2021.10

深層学習とディジタルファントムを用いた骨陰影低減技術の開発

五島 風汰, 田中 利恵, 小田 昌宏, 森 健策, 高田 宗尚, 田村 昌也, 松本 勲

第40回日本医用画像工学会大会予稿集     page： 270 - 272   2021.10

3D Kidney Tumor Semantic Segmentation using Cascaded Convolutional Networks Invited Reviewed

第40回日本医用画像工学会大会予稿集     page： 243 - 248   2021.10

Attention 機構を導入したグラフニューラルネットワークによる,

出口 智也, 林 雄一郎, 北坂 孝幸, 小田 昌宏,1 三澤 一成, 森 健策

第40回日本医用画像工学会大会予稿集     page： 239 - 241   2021.10

深度情報を利用した FCN による腹腔鏡映像からの血管領域自動抽出の検討

榎本 圭吾, 林 雄一郎, 北坂 孝幸, 小田 昌宏,1 伊藤 雅昭, 竹下 修由, 三澤 一成, 森 健策

第40回日本医用画像工学会大会予稿集     page： 235 - 241   2021.10

Vascular Structure Segmentation in Stereomicroscope Image

Yunheng WU, Masahiro ODA, Yuichiro HAYASHI, Takanori TAKEBE, Kensaku MORI

    page： 229 - 234   2021.10

Synthesized Perforation Detection from Endoscopy Videos Using Model Training with Synthesized Images by GAN

Kai Jiang, Hayato Itoh, Masahiro Oda, Taishi Okumura, Yuichi Mori, Masashi Misawa, Takemasa Hayashi, Shin-Ei Kudo, Kensaku Mori

    page： 199 - 201   2021.10

Improving Classification Accuracy of Hands' Bone Marrow Edema by Transfer Learning

Dongping PAN, Masahiro ODA, Kou KATAYAMA, Takanobu Okubo, Kensaku MORI

    page： 150 - 157   2021.10

腸閉塞・イレウスの病変箇所特定における診断支援システムの精度評価

小田 紘久, 林 雄一郎, 北坂 孝幸, 玉田 雄大, 滝本 愛太朗, 檜 顕成, 内田 広夫, 鈴木 耕次郎, 小田 昌宏, 森 健策

第40回日本医用画像工学会大会予稿集     page： 129 - 131   2021.10

Self-attention Class Balanced DenseNet_LSTM framework for Subarachnoid Hemorrhage CT image Classification on Extremely Imbalanced Brain CT Dataset

第40回日本医用画像工学会大会予稿集     page： 69 - 75   2021.10

VR Organ Puzzle: A Virtual Reality Application for the Education of Human Anatomy

Siqi LI, Yuichiro HAYASHI，Michitaka FUJIWARA, Masahiro ODA, Kensaku MORI

    page： 493 - 498   2021.10

Multi-task Federated Learning for Heterogeneous Pancreas Segmentation Invited Reviewed International coauthorship

Chen Shen, Pochuan Wang, Holger R. Roth, Dong Yang, Daguang Xu, Masahiro Oda, Weichung Wang, Chiou-Shann Fuh, Po-Ting Chen, Kao-Lang Liu, Wei-Chih Liao, Kensaku Mori

LNCS12969     page： 101 - 110   2021.9

　More details

DOI： 10.1007/978-3-030-90874-4_10

Super-Resolution by Latent Space Exploration: Training with Poorly-Aligned Clinical and Micro CT Image Dataset Invited Reviewed

Tong Zheng, Hirohisa Oda, Yuichiro Hayashi, Shota Nakamura, Masahiro Oda, Kensaku Mori

LNCS12965     page： 24 - 33   2021.9

Intestine segmentation with small computational cost for diagnosis assistance of ileus and intestinal obstruction Invited Reviewed

Hirohisa Oda, Yuichiro Hayashi, Takayuki Kitasaka, Aitaro Takimoto, Akinari Hinoki, Hiroo Uchida, Kojiro Suzuki, Masahiro Oda, Kensaku Mori

LNCS 12969     page： 3 - 12   2021.9

　More details

DOI： 10.1007/978-3-030-90874-4_1

泌尿器科領域における画像処理

森 健策

泌尿器科   Vol. 14 ( 2 ) page： 213 - 220   2021.8

Can artificial intelligence help to detect dysplasia in patients with ulcerative colitis? Invited International journal

Yasuharu Maeda, Shin-Ei Kudo, Noriyuki Ogata, Masashi Misawa, Yuichi Mori, Kensaku Mori, Kazuo Ohtsuka

Endoscopy   Vol. 53 ( 07 ) page： E273 - E274   2021.7

　More details

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

DOI： 10.1055/a-1261-2944

Web of Science

Scopus

PubMed

Micro-CT-assisted cross-modality super-resolution of clinical CT: utilization of synthesized training dataset Reviewed

T. Zheng, H. Oda, S. Nakamura, M. Mori, H. Takabatake, H. Natori, M. Oda, K. Mori

International Journal of Computer Assisted Radiology and Surgery   Vol. 16 ( sup.1 ) page： 12 - 14   2021.6

Unsupervised colonoscopic depth estimation by domain translations with a Lambertian-reflection keeping auxiliary task Invited Reviewed

Hayato Itoh, Masahiro Oda, Yuichi Mori, Masashi Misawa, Shin-Ei Kudo, Kenichiro Imai, Sayo Ito, Kinichi Hotta, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Kensaku Mori

INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY   Vol. 16 ( 6 ) page： 989 - 1001   2021.6

　More details

Language：English   Publishing type：Research paper (scientific journal)   Publisher：SPRINGER HEIDELBERG  

Purpose A three-dimensional (3D) structure extraction technique viewed from a two-dimensional image is essential for the development of a computer-aided diagnosis (CAD) system for colonoscopy. However, a straightforward application of existing depth-estimation methods to colonoscopic images is impossible or inappropriate due to several limitations of colonoscopes. In particular, the absence of ground-truth depth for colonoscopic images hinders the application of supervised machine learning methods. To circumvent these difficulties, we developed an unsupervised and accurate depth-estimation method. Method We propose a novel unsupervised depth-estimation method by introducing a Lambertian-reflection model as an auxiliary task to domain translation between real and virtual colonoscopic images. This auxiliary task contributes to accurate depth estimation by maintaining the Lambertian-reflection assumption. In our experiments, we qualitatively evaluate the proposed method by comparing it with state-of-the-art unsupervised methods. Furthermore, we present two quantitative evaluations of the proposed method using a measuring device, as well as a new 3D reconstruction technique and measured polyp sizes. Results Our proposed method achieved accurate depth estimation with an average estimation error of less than 1 mm for regions close to the colonoscope in both of two types of quantitative evaluations. Qualitative evaluation showed that the introduced auxiliary task reduces the effects of specular reflections and colon wall textures on depth estimation and our proposed method achieved smooth depth estimation without noise, thus validating the proposed method. Conclusions We developed an accurate depth-estimation method with a new type of unsupervised domain translation with the auxiliary task. This method is useful for analysis of colonoscopic images and for the development of a CAD system since it can extract accurate 3D information.

DOI： 10.1007/s11548-021-02398-x

Web of Science

Scopus

PubMed

AIによる内視鏡外科手術支援と開発基盤としての手術動画データベース構築 Invited Reviewed

竹下 修由, 森 健策, 伊藤 正昭

消化器外科   Vol. 44 ( 7 ) page： 1159 - 1166   2021.6

Three-dimensional surgical plan printing for assisting liver surgery, Reviewed

Y. Hayashi, T. Igami, Y. Nakamura, K. Mori

International Journal of Computer Assisted Radiology and Surgery   Vol. 16 ( sup.1 ) page： 104 - 106   2021.6