KALM: Key Area Localization Mechanism for Abnormality Detection in Musculoskeletal Radiographs

Wei Huang, Zhitong Xiong, Qi Wang, Xuelong Li

科研成果: 书/报告/会议事项章节会议稿件同行评审

5 引用 (Scopus)

摘要

Recently abnormality detection in musculoskeletal radio-graphs has attracted many attentions. For abnormality detection, it is crucial to locate the most important area in the musculoskeletal radiographs. To achieve this goal, we propose a key area localization mechanism (KALM) for abnormality detection for the first time in this paper. The proposed KALM explicitly defines the process of selecting the most important area from the whole image with using only image-level label. Based on KALM, we further present a joint global and local feature representation strategy for abnormality detection which takes as input both the entire image and the selected local area. The experimental results based on several classical convolutional neural network (CNN) architectures of MURA, the largest abnormality detection dataset of musculoskeletal radiographs, demonstrate the effectiveness of our KALM.

源语言英语
主期刊名2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings
出版商Institute of Electrical and Electronics Engineers Inc.
1399-1403
页数5
ISBN(电子版)9781509066315
DOI
出版状态已出版 - 5月 2020
活动2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Barcelona, 西班牙
期限: 4 5月 20208 5月 2020

出版系列

姓名ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
2020-May
ISSN(印刷版)1520-6149

会议

会议2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
国家/地区西班牙
Barcelona
时期4/05/208/05/20

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