论文详情
- 英文标题
- Unified Brain Surface and Volume Registration
- 作者
- Mazdak Abulnaga, Andrew Hoopes, Malte Hoffmann, Robin Magnet, Maks Ovsjanikov, Lilla Zollei, John Guttag, Bruce Fischl, Adrian V Dalca
- 期刊/会议
- ICLR 2026 Poster
- 发表年份
- 2026 年
- 研究方向
- 医学影像
ICLR 2026 Poster accepted paper at ICLR 2026. Accurate registration of brain MRI scans is fundamental for cross-subject analysis in neuroscientific studies. This involves aligning both the cortical surface of the brain and the interior volume. Traditional methods treat volumetric and surface-based registration separately, which often leads to inconsistencies that limit downstream analyses. We propose a deep learning framework, UCS, that registers 3D brain MRI images by jointly aligning both cortical and subcortical regions, through a unified volume-and-surface-based representation. Our approach leverages an intermediate spherical coordinate space to bridge anatomical surface topology with volumetric anatomy, enabling consistent and anatomically accurate alignment.
