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Deep Learning for Diagnosing Developmental Dysplasia of the Hip

      To resolve the temporal diversity and pathological deformity challenge in X-ray based diagnosis of DDH, convert the detection of a landmark to the detection/segmentation of the landmark’s local neighborhood patch. Spatial attention and Adversarial learning are also employed to deal with the false positive detection.

Deep Learning for Pediatric Bone Age Assessment

      Propose a novel weakly-supervised learning approach for Bone Age Assessment, which can discover and extract the discriminative bone parts without human prior. State-of-art performance has been achieved, and the proposed method exhibits interpretability, consistency and inspiration with human prior knowledge.