{"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/staingan-stain-style-transfer-for-digital","title":"StainGAN: Stain Style Transfer for Digital Histological Images","arxiv_id":"1804.01601","date":"2018-04-04","proceeding":null,"authors":["M Tarek Shaban","Christoph Baur","Nassir Navab","Shadi Albarqouni"],"abstract":"Digitized Histological diagnosis is in increasing demand. However, color\nvariations due to various factors are imposing obstacles to the diagnosis\nprocess. The problem of stain color variations is a well-defined problem with\nmany proposed solutions. Most of these solutions are highly dependent on a\nreference template slide. We propose a deep-learning solution inspired by\nCycleGANs that is trained end-to-end, eliminating the need for an expert to\npick a representative reference slide. Our approach showed superior results\nquantitatively and qualitatively against the state of the art methods (10%\nimprovement visually using SSIM). We further validated our method on a clinical\nuse-case, namely Breast Cancer tumor classification, showing 12% increase in\nAUC. The code will be made publicly available.","url_abs":"http://arxiv.org/abs/1804.01601v1","url_pdf":"http://arxiv.org/pdf/1804.01601v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"staingan-stain-style-transfer-for-digital","repo_url":"https://github.com/xtarx/StainGAN","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"ssim","task_name":"SSIM"},{"task_slug":"style-transfer","task_name":"Style Transfer"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1804.01601","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}