{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/medsegdiff-v2-diffusion-based-medical-image","title":"MedSegDiff-V2: Diffusion based Medical Image Segmentation with Transformer","arxiv_id":"2301.11798","date":"2023-01-19","proceeding":null,"authors":["Junde Wu","Wei Ji","Huazhu Fu","Min Xu","Yueming Jin","Yanwu Xu"],"abstract":"The Diffusion Probabilistic Model (DPM) has recently gained popularity in the field of computer vision, thanks to its image generation applications, such as Imagen, Latent Diffusion Models, and Stable Diffusion, which have demonstrated impressive capabilities and sparked much discussion within the community. 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