Medical Image Classification Using Self-Supervised Learning-Based Masked Autoencoder

Zong Fan, Zhimin Wang, Ping Gong, Christine U. Lee, Shanshan Tang, Xiaohui Zhang, Yao Hao, Zhongwei Zhang, Pengfei Song, Shigao Chen, Hua Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Accurate classification of medical images is crucial for disease diagnosis and treatment planning. Deep learning (DL) methods have gained increasing attention in this domain. However, DL-based classification methods encounter challenges due to the unique characteristics of medical image datasets, including limited amounts of labeled images and large image variations. Self-supervised learning (SSL) has emerged as a solution that learns informative representations from unlabeled data to alleviate the scarcity of labeled images and improve model performance. A recently proposed generative SSL method, masked autoencoder (MAE), has shown excellent capability in feature representation learning. The MAE model trained on unlabeled data can be easily tuned to improve the performance of various downstream classification models. In this paper, we performed a preliminary study to integrate MAE with the self-attention mechanism for tumor classification on breast ultrasound (BUS) data. Considering the speckle noise, image quality variations of BUS images, and varying tumor shapes and sizes, two revisions were adopted in using MAE for tumor classification. First, MAE’s patch size and masking ratio were adjusted to avoid missing information embedded in small lesions on BUS images. Second, attention maps were extracted to improve the interpretability of the model’s decision-making process. Experiments demonstrated the effectiveness and potential of the MAE-based classification model on small labeled datasets.

Original languageEnglish
Title of host publicationMedical Imaging 2024
Subtitle of host publicationImage Processing
EditorsOlivier Colliot, Jhimli Mitra
ISBN (Electronic)9781510671560
StatePublished - 2024
EventMedical Imaging 2024: Image Processing - San Diego, United States
Duration: Feb 19 2024Feb 22 2024

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
ISSN (Print)1605-7422


ConferenceMedical Imaging 2024: Image Processing
Country/TerritoryUnited States
CitySan Diego


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