Awesome-Diffusion-Models-in-Medical-Imaging and MedSegDiff
About Awesome-Diffusion-Models-in-Medical-Imaging
amirhossein-kz/Awesome-Diffusion-Models-in-Medical-Imaging
Diffusion Models in Medical Imaging (Published in Medical Image Analysis Journal)
This resource curates a collection of research papers focused on Diffusion Models specifically for medical imaging applications. It provides an overview of various uses, such as anomaly detection, denoising, and image generation, within radiology and other medical fields. Medical researchers, imaging scientists, and AI practitioners in healthcare would find this valuable for staying current with advanced image analysis techniques.
About MedSegDiff
ImprintLab/MedSegDiff
Using Diffusion Models to Segment/Reconstruct Organs from Medical Images [AAAI Most influential Paper]
This project helps medical professionals, researchers, and imaging specialists accurately identify and outline organs or tissues within medical scans like MRIs or skin images. You input medical images (e.g., JPEG, NIfTI files), and it outputs precise segmented images where specific anatomical structures or anomalies are clearly highlighted. This is useful for tasks requiring detailed boundary detection, such as tumor delineation or anatomical measurement.
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