Qiukunpeng/Siamese-Diffusion
[CVPR 2025] Noise-Consistent Siamese-Diffusion for Medical Image Synthesis and Segmentation
This project helps medical professionals and researchers improve the accuracy of medical image analysis, especially for conditions like polyps or skin lesions. It takes existing medical images and generates high-quality synthetic images and their corresponding segmentation masks, which are crucial for training and evaluating diagnostic AI models. Medical imaging specialists, radiologists, and AI model developers in healthcare would find this useful.
Use this if you need to generate realistic medical images and their precise segmentation masks to augment limited datasets or improve the performance of your medical image analysis AI models.
Not ideal if you are looking for a tool to directly analyze patient images for diagnosis; this project focuses on data generation for model training and research.
Stars
87
Forks
7
Language
Python
License
MIT
Category
Last pushed
Nov 29, 2025
Commits (30d)
0
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