Attention-based multiple instance learning for lung neoplasm detection using scleral images

Chuxiang Gao; Zongqing Ma; Hantao Bai; Jiang Zhu

doi:10.1117/12.3036065

20 November 2024 Attention-based multiple instance learning for lung neoplasm detection using scleral images

Chuxiang Gao, Zongqing Ma, Hantao Bai, Jiang Zhu

Author Affiliations +

Proceedings Volume 13242, Optics in Health Care and Biomedical Optics XIV; 1324220 (2024) https://doi.org/10.1117/12.3036065
Event: SPIE/COS Photonics Asia, 2024, Nantong, Jiangsu, China

Conference Poster

Abstract

Lung cancer is one of the most fatal malignant tumors globally. Recent research has revealed that the scleral image, which can be obtained in a painless and non-invasive manner conveniently, is associated with lung cancer. The current method treats the malignant lung neoplasm detection task as a binary classification problem. It takes the multiple images of one subject’s eyes as different instances, and takes the subject as a bag, then employs the multiple instance learning technique to solve the problem. However, the current method utilizes average pooling to aggregate information on different instances in a bag, which overlooks the varying contribution of each instance to the bag label. In this study, we propose an attentionbased multiple instance learning (AMIL) model for lung neoplasm detection using scleral images. The model first employs a convolutional neural network-based backbone to extract features from each scleral image of the subject, then leverages a channel attention module to recalibrate the weight and aggregate the extracted features adaptively. Finally, a fully connection-based classification module is used to make the final prediction for the subject. The results show that the model can effectively identify the critical instances with the help of the attention mechanism, and improve the classification accuracy.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Chuxiang Gao, Zongqing Ma, Hantao Bai, and Jiang Zhu "Attention-based multiple instance learning for lung neoplasm detection using scleral images", Proc. SPIE 13242, Optics in Health Care and Biomedical Optics XIV, 1324220 (20 November 2024); https://doi.org/10.1117/12.3036065

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE