Presentation 2019-01-23
Influence of group normalization in multi-class organ segmentation of abdominal CT volumes
Chen Shen, Fausto Milletari, Holger R. Roth, Hirohisa Oda, Masahiro Oda, Yuichiro Hayashi, Kazunari Misawa, Kensaku Mori,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Organ segmentation is one of the most important branches of medical image analysis. Fully convolutional networks (FCNs) have become the dominant approach for this task and achieved considerable improvements for automated organ segmentation in volumetric image data, such as computed tomography images. In this paper, we investigate the influence of group normalization (GN) in multi-class organ segmentation from 3D CT volumes using fully convolutional network. Batch normalization is widely utilized in deep learning based methods to accelerate the convergence, reduce the reliance on initial learning rate and avoid overfitting. However, this type of normalization is strongly related to the batch size. Here, we study the influence of GN which is independent from batch size. In this research, we performed experiments on 377 cases of portal vein-phase abdominal CT volumes. The segmentation performance for small organs like artery and pancreas improved by introducing GN.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) deep learning / multi-organ segmentation / group normalization / computed tomography
Paper # MI2018-94
Date of Issue 2019-01-15 (MI)

Conference Information
Committee MI
Conference Date 2019/1/22(2days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English) Medical Image Engineering, Analysis, Recognition, etc.
Chair Kensaku Mori(Nagoya Univ.)
Vice Chair Yoshiki Kawata(Tokushima Univ.) / Yuichi Kimura(Kinki Univ.)
Secretary Yoshiki Kawata(Aichi Inst. of Tech.) / Yuichi Kimura(Nagoya Inst. of Tech.)
Assistant Ryo Haraguchi(Univ. of Hyogo) / Yasushi Hirano(Yamaguchi Univ.)

Paper Information
Registration To Medical Imaging
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Influence of group normalization in multi-class organ segmentation of abdominal CT volumes
Sub Title (in English)
Keyword(1) deep learning
Keyword(2) multi-organ segmentation
Keyword(3) group normalization
Keyword(4) computed tomography
1st Author's Name Chen Shen
1st Author's Affiliation Nagoya University(Nagoya Univ.)
2nd Author's Name Fausto Milletari
2nd Author's Affiliation Nvidia(Nvidia)
3rd Author's Name Holger R. Roth
3rd Author's Affiliation Nvidia(Nvidia)
4th Author's Name Hirohisa Oda
4th Author's Affiliation Nagoya University(Nagoya Univ.)
5th Author's Name Masahiro Oda
5th Author's Affiliation Nagoya University(Nagoya Univ.)
6th Author's Name Yuichiro Hayashi
6th Author's Affiliation Nagoya University(Nagoya Univ.)
7th Author's Name Kazunari Misawa
7th Author's Affiliation Aichi Cancer Center Hospital(Aichi Cancer Center Hospital)
8th Author's Name Kensaku Mori
8th Author's Affiliation Nagoya University(Nagoya Univ.)
Date 2019-01-23
Paper # MI2018-94
Volume (vol) vol.118
Number (no) MI-412
Page pp.pp.143-148(MI),
#Pages 6
Date of Issue 2019-01-15 (MI)