研究者詳細 - 小田　昌宏

論文 - 小田　昌宏

分割表示 372 件中 281 - 300 件目／全件表示 >>

Develop and Validate a Finite Element Method Model for Deformation Matching of Laparoscopic Gastrectomy Navigation 査読有り

Chen Tao, Wei Guodong, Shi Weili, Hayashi Yuichiro, Oda Masahiro, Jiang Zhengang, Li Guoxin, Mori Kensaku

MEDICAL IMAGING 2018: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING 10576 巻 2018年

デスクトップ型マイクロCTによる微細解剖構造イメージング招待有り

森健策, 中村彰太, 秋田利明, 小田紘久, ホルガーロス, 小田昌宏

Ｍｅｄｉｃａｌ　Ｉｍａｇｉｎｇ　Ｔｅｃｈｎｏｌｏｇｙ 36 巻 ( 3 ) 頁： 127-132 2018年

記述言語：日本語掲載種別：研究論文（研究会，シンポジウム資料等）

本稿では，デスクトップ型マイクロCTを用いた微細構造イメージングについて述べる．臨床の場で利用されるX線CT装置は，その解像度がおおよそ1ボクセルあたり0.5mmから1mm程度である．このようなイメージング装置を用いて得ることができる画像は，このボクセル解像度に準じた解剖構造を得ることができる．一方，マイクロCT装置を用いれば，1μmから50μm程度の解像度で撮影できる．本稿では，マイクロCTによって撮影された肺標本ならびに心臓標本を示し，その可能性について述べる．

DOI： 10.11409/mit.36.127

CiNii Research

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 36 巻 ( 3 ) 頁： 133-146 2018年

記述言語：英語掲載種別：研究論文（学術雑誌）

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

CiNii Research

A Multi-scale Pyramid of 3D Fully Convolutional Networks for Abdominal Multi-organ Segmentation 査読有り

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 11073 巻頁： 417 - 425 2018年

医用画像処理におけるディープラーニング利用入門-序文- 招待有り

小田昌宏

Ｍｅｄｉｃａｌ　Ｉｍａｇｉｎｇ　Ｔｅｃｈｎｏｌｏｇｙ 36 巻 ( 2 ) 頁： 45 - 46 2018年

Towards Automated Colonoscopy Diagnosis: Binary Polyp Size Estimation via Unsupervised Depth Learning 査読有り

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 11071 巻頁： 611 - 619 2018年

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

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

MEDICAL IMAGING 2018: IMAGE PROCESSING 10574 巻 2018年

Unsupervised Pathology Image Segmentation Using Representation Learning with Spherical K-means 査読有り Open Access

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

MEDICAL IMAGING 2018: DIGITAL PATHOLOGY 10581 巻 2018年

Unsupervised Segmentation of 3D Medical Images Based on Clustering and Deep Representation Learning 査読有り Open Access

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

MEDICAL IMAGING 2018: BIOMEDICAL APPLICATIONS IN MOLECULAR, STRUCTURAL, AND FUNCTIONAL IMAGING 10578 巻 2018年

ディープラーニング活用の重要ポイント招待有り

小田昌宏

Ｍｅｄｉｃａｌ　Ｉｍａｇｉｎｇ　Ｔｅｃｈｎｏｌｏｇｙ 36 巻 ( 2 ) 頁： 72-75 2018年

担当区分：筆頭著者記述言語：日本語掲載種別：研究論文（研究会，シンポジウム資料等）

ディープラーニングは医用画像処理のさまざまなタスク解決に使用することができる便利な手法である．ディープラーニングを研究で活用し，その性能を引き出すために注意を払うべき点がいくつかある．その中で，ディープラーニングにおける多数の手動指定パラメーターの選択，データオーギュメンテーションを使用する上で注意する点，ディープラーニングのランダム要素が与える影響について解説する．

DOI： 10.11409/mit.36.72

CiNii Research

Automatic segmentation of eyeball structures from micro-CT images based on sparse annotation 査読有り

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 10578 巻 2018年

Fully Convolutional Network-Based Eyeball Segmentation from Sparse Annotation for Eye Surgery Simulation Model 査読有り

Sugino Takaaki, Roth Holger R., Oda Masahiro, Mori Kensaku

International Workshop on Bio-Imaging and Visualization for Patient-Customized Simulations, BIVPCS 2018 11042 巻頁： 118-126 2018年

Fine Segmentation of Tiny Blood Vessel Based on Fully-Connected Conditional Random Field 査読有り

Wang Chenglong, Oda Masahiro, Yoshino Yasushi, Yamamoto Tokunori, Mori Kensaku

MEDICAL IMAGING 2018: IMAGE PROCESSING 10574 巻 2018年

Dense volumetric detection and segmentation of mediastinal lymph nodes in chest CT images 査読有り

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

MEDICAL IMAGING 2018: COMPUTER-AIDED DIAGNOSIS 10575 巻 2018年

Deep Learning and Its Application to Medical Image Segmentation 招待有り

ROTH Holger R., SHEN Chen, ODA Hirohisa, ODA Masahiro, HAYASHI Yuichiro, MISAWA Kazunari, MORI Kensaku

Medical Imaging Technology 36 巻 ( 2 ) 頁： 63-71 2018年

記述言語：英語掲載種別：研究論文（研究会，シンポジウム資料等）

One of the most common tasks in medical imaging is semantic segmentation. Achieving this segmentation automatically has been an active area of research, but the task has been proven very challenging due to the large variation of anatomy across different patients. However, recent advances in deep learning have made it possible to significantly improve the performance of image recognition and semantic segmentation methods in the field of computer vision. Due to the data driven approaches of hierarchical feature learning in deep learning frameworks, these advances can be translated to medical images without much difficulty. Several variations of deep convolutional neural networks have been successfully applied to medical images. Especially fully convolutional architectures have been proven efficient for segmentation of 3D medical images. In this article, we describe how to build a 3D fully convolutional network (FCN) that can process 3D images in order to produce automatic semantic segmentations. The model is trained and evaluated on a clinical computed tomography (CT) dataset and shows stateof-the-art performance in multi-organ segmentation.

DOI： 10.11409/mit.36.63

CiNii Research

Cascade classification of endocytoscopic images of colorectal lesions for automated pathological diagnosis 査読有り

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

MEDICAL IMAGING 2018: COMPUTER-AIDED DIAGNOSIS 10575 巻 2018年

BESNet: Boundary-Enhanced Segmentation of Cells in Histopathological Images 査読有り

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 11071 巻頁： 228-236 2018年

Machine learning-based colon deformation estimation method for colonoscope tracking 査読有り Open Access

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 10576 巻 2018年

低ばね剛性機械構造を利用した積層造形臓器モデルの CNC 砥粒加工技術の開発

大庭孝之, 鈴木教和, 社本英二, 小田昌宏, 森健策, 竹内芳美

生産加工・工作機械部門講演会 : 生産と加工に関する学術講演会 2018.12 巻 ( 0 ) 頁： C20 2018年

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

MI2017-51 117 巻 ( 281 ) 頁： 15-20 2017年11月

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