3 citations · 4 across the 5 of their papers we have counts for
5 papers
Emerging Semantic Segmentation from Positive and Negative Coarse Label Learning
Le Zhang, Fuping Wu, Arun Thirunavukarasu +3
Large annotated datasets are vital for training segmentation models, but pixel-level labeling is time-consuming, error-prone, and often requires scarce expert annotators, especiall…
Rethinking Foundation Models for Medical Image Classification through a Benchmark Study on MedMNIST
Fuping Wu, Bartlomiej W. Papiez
Foundation models are widely employed in medical image analysis, due to their high adaptability and generalizability for downstream tasks. With the increasing number of foundation…
KneeXNeT: An Ensemble-Based Approach for Knee Radiographic Evaluation
Nicharee Srikijkasemwat, Soumya Snigdha Kundu, Fuping Wu +1
Knee osteoarthritis (OA) is the most common joint disorder and a leading cause of disability. Diagnosing OA severity typically requires expert assessment of X-ray images and is com…
Deformation-Recovery Diffusion Model (DRDM): Instance Deformation for Image Manipulation and Synthesis
Jian-Qing Zheng, Yuanhan Mo, Yang Sun +5
In medical imaging, the diffusion models have shown great potential for synthetic image generation tasks. However, these approaches often lack the interpretable connections between…
Multi-Task Cooperative Learning via Searching for Flat Minima
Fuping Wu, Le Zhang, Yang Sun +3
Multi-task learning (MTL) has shown great potential in medical image analysis, improving the generalizability of the learned features and the performance in individual tasks. Howev…