Presentation | 2022-09-15 Learning of Squamous Cell Image Classification Model Using Preference Learning to Assist Cervical Cytology Yuta Nambu, Tasuku Mariya, Syota Shinkai, Mina Umemoto, Hiroko Asanuma, Yoshihiko Hirohashi, Tsuyoshi Saito, Toshihiko Torigoe, Ikuma Sato, Yuichi Fujino, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | To support cervical cell diagnosis, Various classification methods of cervical cell images using machine learning have been proposed. However, even methods with large amounts of data and large models have not been able to achieve classification with sufficient performance. One reason for this difficulty may be that label noise tends to occur due to the difficulty of making decisions. Therefore, we propose preference learning of a model that discriminates order relationships among cell images using pairwise data such that `Image B is more malignant than Image A' as labels. In this paper, we report the performance of a deep learning model with preference learning on cervical cell images, and compare the discriminative performance of the model with classification learning. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Cell image classification / Learning to rank / Deep learning |
Paper # | MI2022-62 |
Date of Issue | 2022-09-08 (MI) |
Conference Information | |
Committee | MI |
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Conference Date | 2022/9/15(1days) |
Place (in Japanese) | (See Japanese page) |
Place (in English) | |
Topics (in Japanese) | (See Japanese page) |
Topics (in English) | |
Chair | Hidekata Hontani(Nagoya Inst. of Tech.) |
Vice Chair | Hideaki Haneishi(Chiba Univ.) / Takayuki Kitasaka(Aichi Inst. of Tech.) |
Secretary | Hideaki Haneishi(Yamaguchi Univ.) / Takayuki Kitasaka(Univ. of Hyogo) |
Assistant | Takeshi Hara(Gifu Univ.) / Yoshito Otake(NAIST) |
Paper Information | |
Registration To | Technical Committee on Medical Imaging |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Learning of Squamous Cell Image Classification Model Using Preference Learning to Assist Cervical Cytology |
Sub Title (in English) | |
Keyword(1) | Cell image classification |
Keyword(2) | Learning to rank |
Keyword(3) | Deep learning |
1st Author's Name | Yuta Nambu |
1st Author's Affiliation | Graduate School of Media Architecture, Future University Hakodate, Hakodate, Japan.(Future Univ. Hakodate) |
2nd Author's Name | Tasuku Mariya |
2nd Author's Affiliation | Department of Obstetrics and Gynecology, Sapporo Medical University School of Medicine, Sapporo, Japan.(Sapporo Medical Univ.) |
3rd Author's Name | Syota Shinkai |
3rd Author's Affiliation | Department of Obstetrics and Gynecology, Sapporo Medical University School of Medicine, Sapporo, Japan.(Sapporo Medical Univ.) |
4th Author's Name | Mina Umemoto |
4th Author's Affiliation | Department of Obstetrics and Gynecology, Sapporo Medical University School of Medicine, Sapporo, Japan.(Sapporo Medical Univ.) |
5th Author's Name | Hiroko Asanuma |
5th Author's Affiliation | Department of Pathology 1st, Sapporo Medical University School of Medicine, Sapporo, Japan.(Sapporo Medical Univ.) |
6th Author's Name | Yoshihiko Hirohashi |
6th Author's Affiliation | Department of Pathology 1st, Sapporo Medical University School of Medicine, Sapporo, Japan.(Sapporo Medical Univ.) |
7th Author's Name | Tsuyoshi Saito |
7th Author's Affiliation | Department of Obstetrics and Gynecology, Sapporo Medical University School of Medicine, Sapporo, Japan.(Sapporo Medical Univ.) |
8th Author's Name | Toshihiko Torigoe |
8th Author's Affiliation | Department of Pathology 1st, Sapporo Medical University School of Medicine, Sapporo, Japan.(Sapporo Medical Univ.) |
9th Author's Name | Ikuma Sato |
9th Author's Affiliation | Department of Media Architecture, Future University Hakodate, Hakodate, Japan.(Future Univ. Hakodate) |
10th Author's Name | Yuichi Fujino |
10th Author's Affiliation | Department of Media Architecture, Future University Hakodate, Hakodate, Japan.(Future Univ. Hakodate) |
Date | 2022-09-15 |
Paper # | MI2022-62 |
Volume (vol) | vol.122 |
Number (no) | MI-188 |
Page | pp.pp.53-58(MI), |
#Pages | 6 |
Date of Issue | 2022-09-08 (MI) |