Toward New-Generation AI-Based CAD System: Development of Interpretable Deep Learning-Based CAD System for Breast Cancer Diagnosis Using Mammogram

迈向新一代基于人工智能的 CAD 系统：开发可解释的基于深度学习的 CAD 系统，用于使用乳房 X 线照片诊断乳腺癌

• 批准号: 20K08012
• 负责人: 張 暁勇
• 金额: $ 2.75万
• 依托单位: Sendai National College of Technology
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2020
• 资助国家: 日本
• 起止时间: 2020-04-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-20K08012/
• 关键词: Mammograpy; Deep Learning; Explainable AI; Computer-Aided Diagnosis; Lesion Detection; Interpretablity; Breast Cancer; Computer-Aided Detection; Artificial Intellegence

The purpose of this research is to develop an interpretable deep learning (DL)-based computer-aided diagnosis (CAD) system for breast cancer diagnosis in mammogram. On the base of the achivement of FY2021, we achived the following progresses in the FY2022.(1) Experments for evaluation of DL models in lesion detection has been conducted on four mammogram data sets, which were collected in the previous FY.(2) A new training method, which utilized the clinicians's pixel-wise anotation and saliency maps to improve the DL model acuuracy, was proposed and tested.(3) Two papers has been published in the related international journals.

本研究的目的是开发一个可解释的基于深度学习（DL）的计算机辅助诊断（CAD）系统，用于乳房x光检查中的乳腺癌诊断。在2021财年的基础上，我们在2022财年取得了以下进展：(1)在上一财年收集的四组乳腺x线照片数据集上进行了DL模型在病变检测中的评价实验。(2)提出了一种新的训练方法，利用临床医生的逐像素注释和显著性图来提高深度学习模型的准确性，并进行了测试。(3)在国际相关期刊上发表论文2篇。

项目成果

Deep Learning-Based Interpretable Computer Aided Diagnosis of Drowning for Forensic Radiology

基于深度学习的可解释计算机辅助法医放射学溺水诊断

• 发表时间: 2021
• 作者: Yuwen Zeng;Xiaoyong Zhang;et al.
• 通讯作者: et al.

A 2.5D Deep Learning-Based Method for Drowning Diagnosis Using Post-Mortem Computed Tomography

基于 2.5D 深度学习的基于尸检计算机断层扫描的溺水诊断方法

• DOI: 10.1109/jbhi.2022.3225416
• 发表时间: 2023
• 期刊: IEEE Journal of Biomedical and Health Informatics
• 影响因子: 7.7
• 作者: Zeng Yuwen;Zhang Xiaoyong;Kawasumi Yusuke;Usui Akihito;Ichiji Kei;Funayama Masato;Homma Noriyasu
• 通讯作者: Homma Noriyasu

Hidden Markov Model-based Extraction of Target Objects in X-ray Image Sequence for Lung Radiation Therapy

基于隐马尔可夫模型的肺放射治疗X射线图像序列中目标对象的提取

• DOI: 10.1541/ieejeiss.140.49
• 发表时间: 2020
• 期刊: IEEJ Transactions on Electronics, Information and Systems
• 作者: 新藤 雅大;市地 慶;本間 経康;張 曉勇;奥田 隼梧;杉田 典大;八巻 俊輔;髙井 良尋;吉澤 誠
• 通讯作者: 吉澤 誠

Feature Fusionに基づく深層学習を用いた乳房X線画像上の小病変検出

基于特征融合的深度学习对乳房X线照片的小病变检测

• 发表时间: 2020
• 作者: Reima Ishii;Xiaoyong Zhang;Noriyasu Homma;今佑太朗，張暁勇，本間経康，吉澤誠，
• 通讯作者: 今佑太朗，張暁勇，本間経康，吉澤誠，

Improved Tumor Image Estimation in X-Ray Fluoroscopic Images by Augmenting 4DCT Data for Radiotherapy

通过增强放射治疗的 4DCT 数据改进 X 射线透视图像中的肿瘤图像估计

• DOI: 10.20965/jaciii.2022.p0471
• 发表时间: 2022
• 期刊: Journal of Advanced Computational Intelligence and Intelligent Informatics
• 影响因子: 0.7
• 作者: Shinohara Takumi;Ichiji Kei;Wang Jiaoyang;Homma Noriyasu;Zhang Xiaoyong;Sugita Norihiro;Yoshizawa Makoto
• 通讯作者: Yoshizawa Makoto