12 citations · 24 across the 8 of their papers we have counts for
10 papers
Weakly Supervised Online Action Detection for Infant General Movements
Tongyi Luo, Jia Xiao, Chuncao Zhang +5
To make the earlier medical intervention of infants' cerebral palsy (CP), early diagnosis of brain damage is critical. Although general movements assessment(GMA) has shown promisin…
MDT-Net: Multi-domain Transfer by Perceptual Supervision for Unpaired Images in OCT Scan
Weinan Song, Gaurav Fotedar, Nima Tajbakhsh +3
Deep learning models tend to underperform in the presence of domain shifts. Domain transfer has recently emerged as a promising approach wherein images exhibiting a domain shift ar…
Bilateral-ViT for Robust Fovea Localization
Sifan Song, Kang Dang, Qinji Yu +4
The fovea is an important anatomical landmark of the retina. Detecting the location of the fovea is essential for the analysis of many retinal diseases. However, robust fovea local…
A Location-Sensitive Local Prototype Network for Few-Shot Medical Image Segmentation
Qinji Yu, Kang Dang, Nima Tajbakhsh +2
Despite the tremendous success of deep neural networks in medical image segmentation, they typically require a large amount of costly, expert-level annotated data. Few-shot segment…
Learning Differential Diagnosis of Skin Conditions with Co-occurrence Supervision using Graph Convolutional Networks
Junyan Wu, Hao Jiang, Xiaowei Ding +4
Skin conditions are reported the 4th leading cause of nonfatal disease burden worldwide. However, given the colossal spectrum of skin disorders defined clinically and shortage in d…
Extreme Consistency: Overcoming Annotation Scarcity and Domain Shifts
Gaurav Fotedar, Nima Tajbakhsh, Shilpa Ananth +1
Supervised learning has proved effective for medical image analysis. However, it can utilize only the small labeled portion of data; it fails to leverage the large amounts of unlab…