Human ability enhancement for reading mammographic masses by a deep learning technique

Noriyasu Homma, Kyohei Noro, Xiaoyong Zhang, Yutaro Kon, Kei Ichiji, Ivo Bukovsky, Akiko Sato, Naoko Mori

研究成果: Conference contribution

抄録

The usefulness of taking mammography has widely been recognized, but screening mammography occasionally results in an excessive recommendation for subsequent biopsy causing many women inconvenience and severe anxiety. Especially, there is a high chance of unnecessary biopsy recommendation for those findings which are difficult to be classified into malignancy and benignancy. However, few have focused on the computer-aided diagnosis (CAD) performance for such difficult cases. To address this problem, we developed a deep learning based classification technique to aid the difficult diagnosis. We evaluated 100 benign and malignant masses of the breast imaging-reporting and data system (BI-RADS) Category 4 that are generally difficult to be classified into malignant and benign. Five certificated doctors participated in the experiments where each doctor reads the 100 images alone first and a week later reads again with the proposed CAD system. The area under the receiver operating characteristic curve (AUC-ROC) for the CAD system was 0.79. This is greater than 0.65, the average value of the human readers' AUC-ROCs, while the average value of the human readers' AUC-ROCs reached the best value of 0.8 when they used the CAD system. These results suggest that the proposed CAD system is able to not only outperform human readers in classifying the masses, but also enhance the human performance in this difficult task.

本文言語English
ホスト出版物のタイトルProceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020
編集者Taesung Park, Young-Rae Cho, Xiaohua Tony Hu, Illhoi Yoo, Hyun Goo Woo, Jianxin Wang, Julio Facelli, Seungyoon Nam, Mingon Kang
出版社Institute of Electrical and Electronics Engineers Inc.
ページ2962-2964
ページ数3
ISBN(電子版)9781728162157
DOI
出版ステータスPublished - 2020 12 16
イベント2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020 - Virtual, Seoul, Korea, Republic of
継続期間: 2020 12 162020 12 19

出版物シリーズ

名前Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020

Conference

Conference2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020
国/地域Korea, Republic of
CityVirtual, Seoul
Period20/12/1620/12/19

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • 情報システムおよび情報管理
  • 医学(その他)
  • 健康情報学

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