Faculty Profiles - ODA, Masahiro

Papers - ODA, Masahiro

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Cascade classification of endocytoscopic images of colorectal lesions for automated pathological diagnosis Reviewed

Itoh Hayato, Mori Yuichi, Misawa Masashi, Oda Masahiro, Kudo Shin-ei, Mori Kensaku

MEDICAL IMAGING 2018: COMPUTER-AIDED DIAGNOSIS Vol. 10575 2018

BESNet: Boundary-Enhanced Segmentation of Cells in Histopathological Images Reviewed

Oda Hirohisa, Roth Holger R., Chiba Kosuke, Sokolic Jure, Kitasaka Takayuki, Oda Masahiro, Hinoki Akinari, Uchida Hiroo, Schnabel Julia A., Mori Kensaku

MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2018, PT II Vol. 11071 page： 228-236 2018

Automatic segmentation of eyeball structures from micro-CT images based on sparse annotation Reviewed

Sugino Takaaki, Roth Holger R., Oda Masahiro, Omata Seiji, Sakuma Shinya, Arai Fumihito, Mori Kensaku

MEDICAL IMAGING 2018: BIOMEDICAL APPLICATIONS IN MOLECULAR, STRUCTURAL, AND FUNCTIONAL IMAGING Vol. 10578 2018

Airway Segmentation from 3D Chest CT Volumes Based on Volume of Interest Using Gradient Vector Flow

MENG Qier, KITASAKA Takayuki, ODA Masahiro, UENO Junji, MORI Kensaku

Medical Imaging Technology Vol. 36 ( 3 ) page： 133-146 2018

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

In this paper, we propose a new airway segmentation algorithm from 3D chest CT volumes based on the volume of interest (VOI). The algorithm segments each bronchial branch by recognizing the airway regions from the trachea using the VOIs to segment each branch. A VOI is placed to envelop the branch currently being processed. Then a cavity enhancement filter is performed only inside the current VOI so that each branch is extracted. At the same time, we perform a leakage detection scheme to avoid any leakage regions inside the VOI. Next the gradient vector flow magnitude map and a tubular-likeness function are computed in each VOI. This assists the predictions of both the position and direction of the next child VOIs to detect the next child branches to continue the tracking algorithm. Finally, we unify all of the extracted airway regions to form a complete airway tree. We used a dataset that includes 50 standard-dose human chest CT volumes to evaluate our proposed algorithm. The average extraction rate was approximately 78.1% with a significantly decreased false positive rate compared to the previous method.

DOI： 10.11409/mit.36.133

A Multi-scale Pyramid of 3D Fully Convolutional Networks for Abdominal Multi-organ Segmentation Reviewed

Roth Holger R., Shen Chen, Oda Hirohisa, Sugino Takaaki, Oda Masahiro, Hayashi Yuichiro, Misawa Kazunari, Mori Kensaku

MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2018, PT IV Vol. 11073 page： 417 - 425 2018

Guidance of Deep Learning for Medical Image Processing: Introduction Invited

ODA Masahiro

Medical Imaging Technology Vol. 36 ( 2 ) page： 45 - 46 2018

Towards Automated Colonoscopy Diagnosis: Binary Polyp Size Estimation via Unsupervised Depth Learning Reviewed

Itoh Hayato, Roth Holger R., Lu Le, Oda Masahiro, Misawa Masashi, Mori Yuichi, Kudo Shin-ei, Mori Kensaku

MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2018, PT II Vol. 11071 page： 611 - 619 2018

Towards dense volumetric pancreas segmentation in CT using 3D fully convolutional networks

Roth Holger, Oda Masahiro, Shimizu Natsuki, Oda Hirohisa, Hayashi Yuichiro, Kitasaka Takayuki, Fujiwara Michitaka, Misawa Kazunari, Mori Kensaku

MEDICAL IMAGING 2018: IMAGE PROCESSING Vol. 10574 2018

Unsupervised Pathology Image Segmentation Using Representation Learning with Spherical K-means Reviewed

Moriya Takayasu, Roth Holger H., Nakamura Shota, Oda Hirohisa, Nagara Kai, Oda Masahiro, Mori Kensaku

MEDICAL IMAGING 2018: DIGITAL PATHOLOGY Vol. 10581 2018

Machine learning-based colon deformation estimation method for colonoscope tracking Reviewed

Oda Masahiro, Kitasaka Takayuki, Furukawa Kazuhiro, Miyahara Ryoji, Hirooka Yoshiki, Goto Hidemi, Navab Nassir, Mori Kensaku

MEDICAL IMAGING 2018: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING Vol. 10576 2018

Development of a CNC abrasive machining technique for 3D-printed organ models by utilizing a flexible mechanical structure

OHBA Takayuki, SUZUKI Norikazu, SHAMOTO Eiji, ODA Masahiro, MORI Kensaku, TAKEUCHI Yoshimi

The Proceedings of The Manufacturing & Machine Tool Conference Vol. 2018.12 ( 0 ) page： C20 2018

Language：Japanese Publisher：The Japan Society of Mechanical Engineers

This paper presents a novel surface finishing technology for free-formed surfaces of three-dimensional (3D) printed resin organ models. Demand for the medical applications of three-dimensional layered fabrication technology such as organ models is increasing. Surface integrity deteriorations due to laminated micro steps formed on the surface is a significant problem. In general, material removal of layered micro step is performed manually, hence automation technology is desired. In the present study, we proposed a quasi-constant machining force grinding / polishing by use of 3-axis CNC machine tools. The workpiece is fixed to the flexible mechanical structure, whose translational flexibilities are designed to be identical regardless of contact directions and low spring rigidity. With the developed machining system, the liver model processing was demonstrated. Experimental results verified the feasibility of highly-efficient abrasive machining.

DOI： 10.1299/jsmemmt.2018.12.c20

CiNii Research

On the influence of Dice loss function in multi-class organ segmentation of abdominal CT using 3D fully convolutional networks

Chen Shen, Holger R. Roth, Hirohisa Oda, Masahiro Oda, Yuichiro Hayashi, Kazunari Misawa, Kensaku Mori

MI2017-51 Vol. 117 ( 281 ) page： 15-20 2017.11

Study on the Robustness of ORB-SLAM Based Outlier Elimination in Bronchoscope Tracking -- RANSAC + EPnP for Outlier Detection --

Cheng Wang, Masahiro Oda, Yuichiro Hayashi, Hirotoshi Honma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Kensaku Mori

MI2017-58 Vol. 117 ( 281 ) page： 47-52 2017.11

Automated Multi-Organ Segmentation in Abdominal CT with Hierarchical 3D Fully-Convolutional Networks

Holger R. Roth, Hirohisa Oda, MENG, Yuichiro Hayashi, Masahiro Oda, Natsuki Shimizu, Kensaku Mori, Michitaka Fujiwara, Kazunari Misawa

RSNA 2017 (Radiological Society of North America) Scientific Assembly and Annual Meeting PROGRAM IN BRIEF page： 267 2017.11

Automated mediastinal lymph node detection from CT volumes based on intensity targeted radial structure tensor analysis Reviewed International coauthorship

Hirohisa Oda, Kanwal K. Bhatia, Masahiro Oda, Takayuki Kitasaka, Shingo Iwano, Hirotoshi Homma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Julia A. Schnabel, Kensaku Mori

JOURNAL OF MEDICAL IMAGING Vol. 4 ( 4 ) page： 044502 2017.10

3D Fully Convolutional Networks と全連結条件付確率場による 3 次元 CT 画像からの多臓器自動抽出に関する検討

楊瀛, 小田昌宏, Roth Holger, 北坂孝幸, 三澤一成, 森健策

日本コンピュータ外科学会誌第26回日本コンピュータ外科学会大会特集号 Vol. 19 ( 4 ) page： 268-269 2017.10

サポートベクタマシンを用いたラジオミクスベースの消化管間質性腫瘍リスク評価システム

陳韜, 小田紘久, Holger R. Roth, 北坂孝幸, 小田昌宏, 李国新, 森健策

日本コンピュータ外科学会誌第26回日本コンピュータ外科学会大会特集号 Vol. 19 ( 4 ) page： 239-240 2017.10

μCT 画像を用いた大変形を含む連続切片 HE 染色画像の 3 次元再構築

長柄快, Holger Roth, 中村彰太, 小田紘久, 守谷享泰, 小田昌宏, 森健策

日本コンピュータ外科学会誌第26回日本コンピュータ外科学会大会特集号 Vol. 19 ( 4 ) page： 363-364 2017.10

マイクロ CT を用いた膵臓パラフィンブロック標本の解析

進藤幸治, 大内田研宙, Holger R. Roth, 小田紘久, 岩本千佳, 小田昌宏, 中村雅史, 森健策, 橋爪誠

日本コンピュータ外科学会誌第26回日本コンピュータ外科学会大会特集号 Vol. 19 ( 4 ) page： 244-245 2017.10

超拡大大腸内視鏡画像を利用した病理自動診断〜腫瘍性病変に関する分類精度解析〜

伊東隼人, 森悠一, 三澤将史, 小田昌宏, 工藤進英, 森健策

日本コンピュータ外科学会誌第26回日本コンピュータ外科学会大会特集号 Vol. 19 ( 4 ) page： 319-320 2017.10

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Papers - ODA, Masahiro