AsT: An Asymmetric-Sensitive Transformer for Osteonecrosis of the Femoral Head Detection (Student Abstract)
Keywords:Transformer, Early ONFH Detection, FGVC
AbstractEarly diagnosis of osteonecrosis of the femoral head (ONFH) can inhibit the progression and improve femoral head preservation. The radiograph difference between early ONFH and healthy ones is not apparent to the naked eye. It is also hard to produce a large dataset to train the classification model. In this paper, we propose Asymmetric-Sensitive Transformer (AsT) to capture the uneven development of the bilateral femoral head to enable robust ONFH detection. Our ONFH detection is realized using the self-attention mechanism to femoral head regions while conferring sensitivity to the uneven development by the attention-shared transformer. The real-world experiment studies show that AsT achieves the best performance of AUC 0.9313 in the early diagnosis of ONFH and can find out misdiagnosis cases firmly.
How to Cite
Chen, H., Liu, S., Lu, F., Li, W., Sheng, B., Li, M., Jin, H., & Zomaya, A. Y. (2023). AsT: An Asymmetric-Sensitive Transformer for Osteonecrosis of the Femoral Head Detection (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 37(13), 16186-16187. https://doi.org/10.1609/aaai.v37i13.26953
AAAI Student Abstract and Poster Program