{"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/linear-and-deformable-image-registration-with","title":"Linear and Deformable Image Registration with 3D Convolutional Neural Networks","arxiv_id":"1809.06226","date":"2018-09-13","proceeding":null,"authors":["Stergios Christodoulidis","Mihir Sahasrabudhe","Maria Vakalopoulou","Guillaume Chassagnon","Marie-Pierre Revel","Stavroula Mougiakakou","Nikos Paragios"],"abstract":"Image registration and in particular deformable registration methods are\npillars of medical imaging. Inspired by the recent advances in deep learning,\nwe propose in this paper, a novel convolutional neural network architecture\nthat couples linear and deformable registration within a unified architecture\nendowed with near real-time performance. Our framework is modular with respect\nto the global transformation component, as well as with respect to the\nsimilarity function while it guarantees smooth displacement fields. We evaluate\nthe performance of our network on the challenging problem of MRI lung\nregistration, and demonstrate superior performance with respect to state of the\nart elastic registration methods. The proposed deformation (between inspiration\n& expiration) was considered within a clinically relevant task of interstitial\nlung disease (ILD) classification and showed promising results.","url_abs":"http://arxiv.org/abs/1809.06226v1","url_pdf":"http://arxiv.org/pdf/1809.06226v1.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":"linear-and-deformable-image-registration-with","repo_url":"https://github.com/stergioc/smooth-transformer","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}}],"tasks":[{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"image-registration","task_name":"Image Registration"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}