most citedRaffeSDG: Random Frequency Filtering enabled Single-source Domain Generalization for Medical Image Segmentation

3 citations · 3 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Plasticine: A Traceable Diffusion Model for Medical Image Translation

Tianyang Zhang, Xinxing Cheng, Jun Cheng +6

Domain gaps arising from variations in imaging devices and population distributions pose significant challenges for machine learning in medical image analysis. Existing image-to-im…

cs.CV20263 cited

RaffeSDG: Random Frequency Filtering enabled Single-source Domain Generalization for Medical Image Segmentation

Heng Li, Haojin Li, Jianyu Chen +3

Deep learning models often encounter challenges in making accurate inferences when there are domain shifts between the source and target data. This issue is particularly pronounced…

eess.IV2024

Structure Unbiased Adversarial Model for Medical Image Segmentation

Tianyang Zhang, Shaoming Zheng, Jun Cheng +7

Generative models have been widely proposed in image recognition to generate more images where the distribution is similar to that of the real ones. It often introduces a discrimin…

cs.CV2024

CLIP-DR: Textual Knowledge-Guided Diabetic Retinopathy Grading with Ranking-aware Prompting

Qinkai Yu, Jianyang Xie, Anh Nguyen +6

Diabetic retinopathy (DR) is a complication of diabetes and usually takes decades to reach sight-threatening levels. Accurate and robust detection of DR severity is critical for th…

eess.IV2024

Is Dataset Quality Still a Concern in Diagnosis Using Large Foundation Model?

Ziqin Lin, Heng Li, Zinan Li +2

Recent advancements in pre-trained large foundation models (LFM) have yielded significant breakthroughs across various domains, including natural language processing and computer v…