@inproceedings{8d278fd8d4b54f1f9bba8c31cc7d8162,
title = "MSRT: Multi-Scale Spatial Regularization Transformer For Multi-Label Classification in Calcaneus Radiograph",
abstract = "Calcaneus fracture is one of the most common fractures which affect daily life quality. However, calcaneus fracture subtype classification is a challenging task due to the nature of multi-label as well as limited annotated data. In this paper, an augmentation strategy called GridDropInOut (GDIO) is proposed to increase the uncertainty of the rough input mask and enlarge the dataset. A spatial regularization transformer (SRT) is designed to capture labels' spatial information, while a multi-scale attention SRT (MSRT) is built to synthesize spatial features from different levels. Our final proposal achieves an mAP of 87.54\% in classifying six calcaneus fracture types.",
keywords = "Calcaneus Fracture, Multi-label Classification, Multi-scale Attention, Transformer",
author = "Yuxuan Mu and He Zhao and Jia Guo and Huiqi Li",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 19th IEEE International Symposium on Biomedical Imaging, ISBI 2022 ; Conference date: 28-03-2022 Through 31-03-2022",
year = "2022",
doi = "10.1109/ISBI52829.2022.9761435",
language = "English",
series = "Proceedings - International Symposium on Biomedical Imaging",
publisher = "IEEE Computer Society",
booktitle = "ISBI 2022 - Proceedings",
address = "United States",
}