35 citations · 80 across the 15 of their papers we have counts for
4 papers · 1 filter
Hierarchical Self-Supervised Learning for Medical Image Segmentation Based on Multi-Domain Data Aggregation
Hao Zheng, Jun Han, Hongxiao Wang +4
A large labeled dataset is a key to the success of supervised deep learning, but for medical image segmentation, it is highly challenging to obtain sufficient annotated images for…
Image Complexity Guided Network Compression for Biomedical Image Segmentation
Suraj Mishra, Danny Z. Chen, X. Sharon Hu
Compression is a standard procedure for making convolutional neural networks (CNNs) adhere to some specific computing resource constraints. However, searching for a compressed arch…
Objective-Dependent Uncertainty Driven Retinal Vessel Segmentation
Suraj Mishra, Danny Z. Chen, X. Sharon Hu
From diagnosing neovascular diseases to detecting white matter lesions, accurate tiny vessel segmentation in fundus images is critical. Promising results for accurate vessel segmen…
Flow-Mixup: Classifying Multi-labeled Medical Images with Corrupted Labels
Jintai Chen, Hongyun Yu, Ruiwei Feng +2
In clinical practice, medical image interpretation often involves multi-labeled classification, since the affected parts of a patient tend to present multiple symptoms or comorbidi…