Presentation 2017-05-26
Classification of optic disc shape in glaucoma using machine learning based on quantified ocular parameters from ophthalmic examination instruments
Guangzhou An, Kazuko Omodaka, Satoru Tsuda, Yukihiro Shiga, Naoko Takada, Tsutomu Kikawa, Toru Nakazawa, Hideo Yokota, Masahiro Akiba,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) This study aims to classify OAG patients’ optic disc shape objectively. This study enrolled 163 eyes of 105 OAG patients. Four machine learning classifiers, such as Support Vector Machine, Neural Network, Naive Bayes, Gradient Boosting Decision Tree, were applied with a variety of quantified data from ophthalmic examination equipment. As a result of comparing the prediction models’ performance, the accuracy of neural network was the highest, 85.6% validated with test data. It is expected that, the confidence level of the predicted disc types should be very useful for the medical care of patients with OAG.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) glaucoma / optic disc shape / OCT / machine learning / feature selection
Paper # SIP2017-12,IE2017-12,PRMU2017-12,MI2017-12
Date of Issue 2017-05-18 (SIP, IE, PRMU, MI)

Conference Information
Committee PRMU / IE / MI / SIP
Conference Date 2017/5/25(2days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Eisaku Maeda(NTT) / Seishi Takamura(NTT) / Yoshitaka Masutani(Hiroshima City Univ.) / Makoto Nakashizuka(Chiba Inst. of Tech.)
Vice Chair Seiichi Uchida(Kyushu Univ.) / Hironobu Fujiyoshi(Chubu Univ.) / Takayuki Hamamoto(Tokyo Univ. of Science) / Atsuro Ichigaya(NHK) / Yoshiki Kawata(Tokushima Univ.) / Yuichi Kimura(Kinki Univ.) / Masahiro Okuda(Univ. of Kitakyushu) / Shogo Muramatsu(Niigata Univ.)
Secretary Seiichi Uchida(Kyoto Univ.) / Hironobu Fujiyoshi(NTT) / Takayuki Hamamoto(NTT) / Atsuro Ichigaya(Chiba Inst. of Tech.) / Yoshiki Kawata(Aichi Inst. of Tech.) / Yuichi Kimura(Nagoya Inst. of Tech.) / Masahiro Okuda(Ritsumeikan Univ.) / Shogo Muramatsu(Chiba Inst. of Tech.)
Assistant Masaki Oonishi(AIST) / Takuya Funatomi(NAIST) / Kei Kawamura(KDDI R&D Labs.) / Keita Takahashi(Nagoya Univ.) / Ryo Haraguchi(Univ. of Hyogo) / Yasushi Hirano(Yamaguchi Univ.) / Osamu Watanabe(Takushoku Univ.)

Paper Information
Registration To Technical Committee on Pattern Recognition and Media Understanding / Technical Committee on Image Engineering / Technical Committee on Medical Imaging / Technical Committee on Signal Processing
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Classification of optic disc shape in glaucoma using machine learning based on quantified ocular parameters from ophthalmic examination instruments
Sub Title (in English)
Keyword(1) glaucoma
Keyword(2) optic disc shape
Keyword(3) OCT
Keyword(4) machine learning
Keyword(5) feature selection
1st Author's Name Guangzhou An
1st Author's Affiliation TOPCON Corporation/RIKEN(TOPCON/RIKEN)
2nd Author's Name Kazuko Omodaka
2nd Author's Affiliation Tohoku University(Tohoku Univ.)
3rd Author's Name Satoru Tsuda
3rd Author's Affiliation Tohoku University(Tohoku Univ.)
4th Author's Name Yukihiro Shiga
4th Author's Affiliation Tohoku University(Tohoku Univ.)
5th Author's Name Naoko Takada
5th Author's Affiliation Tohoku University(Tohoku Univ.)
6th Author's Name Tsutomu Kikawa
6th Author's Affiliation TOPCON Corporation(TOPCON)
7th Author's Name Toru Nakazawa
7th Author's Affiliation Tohoku University/RIKEN(Tohoku Univ./RIKEN)
8th Author's Name Hideo Yokota
8th Author's Affiliation RIKEN(RIKEN)
9th Author's Name Masahiro Akiba
9th Author's Affiliation TOPCON Corporation/RIKEN(TOPCON/RIKEN)
Date 2017-05-26
Paper # SIP2017-12,IE2017-12,PRMU2017-12,MI2017-12
Volume (vol) vol.117
Number (no) SIP-47,IE-48,PRMU-49,MI-50
Page pp.pp.63-66(SIP), pp.63-66(IE), pp.63-66(PRMU), pp.63-66(MI),
#Pages 4
Date of Issue 2017-05-18 (SIP, IE, PRMU, MI)