ICCV 2025 (PHAROS Workshop)
We are thrilled to announce that our paper titled “𝗗𝗲𝗲𝗽𝗦𝗲𝗴-𝗠𝗦: 𝗔 𝟯𝗗 𝗻𝗲𝘁𝘄𝗼𝗿𝗸 𝗯𝗮𝘀𝗲𝗱 𝗼𝗻 𝗵𝗶𝗲𝗿𝗮𝗿𝗰𝗵𝗶𝗰𝗮𝗹 𝗺𝘂𝗹𝘁𝗶-𝘀𝗰𝗮𝗹𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗳𝗼𝗿 𝗠𝗥𝗜 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝘀𝗰𝗹𝗲𝗿𝗼𝘀𝗶𝘀 𝗹𝗲𝘀𝗶𝗼𝗻 𝘀𝗲𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻” has been accepted at the “𝘗𝘏𝘈𝘙𝘖𝘚 – 𝘈𝘥𝘢𝘱𝘵𝘢𝘵𝘪𝘰𝘯, 𝘍𝘢𝘪𝘳𝘯𝘦𝘴𝘴, 𝘌𝘹𝘱𝘭𝘢𝘪𝘯𝘢𝘣𝘪𝘭𝘪𝘵𝘺 𝘪𝘯 𝘈𝘐 𝘔𝘦𝘥𝘪𝘤𝘢𝘭 𝘐𝘮𝘢𝘨𝘪𝘯𝘨” Workshop, in conjunction with ICCV 2025 (Honolulu, Hawaii)
This work presents 𝗗𝗲𝗲𝗽𝗦𝗲𝗴-𝗠𝗦, a novel 3D deep learning architecture tailored for accurate and robust segmentation of Multiple Sclerosis lesions from multimodal MRI.Our model introduces three key modules:
𝘚𝘲𝘶𝘦𝘦𝘻𝘦-𝘢𝘯𝘥-𝘈𝘵𝘵𝘦𝘯𝘵𝘪𝘰𝘯 𝘣𝘭𝘰𝘤𝘬𝘴 — to enhance focus on relevant lesion regions 𝘋𝘦𝘦𝘱 𝘚𝘶𝘱𝘦𝘳𝘷𝘪𝘴𝘪𝘰𝘯 — for effective hierarchical learning 𝘈𝘵𝘳𝘰𝘶𝘴 𝘚𝘱𝘢𝘵𝘪𝘢𝘭 𝘗𝘺𝘳𝘢𝘮𝘪𝘥 𝘗𝘰𝘰𝘭𝘪𝘯𝘨 — to capture multi-scale contextual features through parallel dilated convolutions
By addressing the spatial complexity and heterogeneity of MS lesions in 3D volumes, 𝗗𝗲𝗲𝗽𝗦𝗲𝗴-𝗠𝗦 pushes forward the capabilities of automated neuroimaging-based analysis.
𝗦𝘁𝗮𝘆 𝘁𝘂𝗻𝗲𝗱 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗼𝗳𝗳𝗶𝗰𝗶𝗮𝗹 𝗽𝗿𝗲𝗽𝗿𝗶𝗻𝘁 𝗮𝗻𝗱 𝗰𝗼𝗱𝗲 𝗿𝗲𝗹𝗲𝗮𝘀𝗲!