各向异性脑部T2加权MRI的解剖学一致跨对比度超分辨率

中文摘要 AI 辅助

T2加权（T2w）脑部MRI提供对流体敏感的软组织对比度，这对神经肿瘤学和放疗规划至关重要。然而，T2w扫描采用各向异性体素采集，在冠状面和矢状面视图上呈现模糊或阶梯状，这会遮挡小结构并削弱任何下游3D分析。我们提出VIPP-SR（视图独立修补投影超分辨率），这是一种跨对比度引导的超分辨率框架，可在无需各向同性真实T2w的情况下，恢复现有各向异性T2w体积的平面间分辨率。VIPP-SR首先训练视图独立修补生成器（VIP-GAN），从高分辨率轴向切片中学习T1c到T2w的解剖对应关系。训练后的生成器随后应用于T1c体积的轴向、冠状面和矢状面视图，以生成三个正交的T2w估计值。保形修补和最深跳跃去除减少了视图特定的捷径，从而约束生成器学习修补局部表示并实现零样本平面间迁移。VIPP-SR的核心是基于投影的优化，它强制三个视图特定体积之间的解剖一致性，通过平衡平面间自一致性与单视图数据保真度来融合这些体积。该生成器在BraTS-MET上进行训练，并在保留的BraTS-MET测试集和BraTS-GLI队列上进行评估，无需重新训练，以评估跨队列的泛化能力。结果验证，VIPP-SR相比真实各向异性T2w基线提升了下游分割性能，在BraTS-MET上平均标签Dice从0.330提升至0.465，在BraTS-GLI上零样本情况下从0.473提升至0.563，消融研究确定平面间自一致性是性能提升的主要来源。

英文摘要

T2-weighted (T2w) brain MRI provides fluid-sensitive soft-tissue contrast that is important for neuro-oncology and radiotherapy planning. However, T2w scans are acquired with anisotropic voxels and appear blurred or stair-stepped on coronal and sagittal views, which obscures small structures and weakens any downstream 3D analysis. We propose VIPP-SR (View-Independent Patched Projection Super-Resolution), a cross-contrast guided super-resolution framework that restores the inter-plane resolution of an existing anisotropic T2w volume without an isotropic ground-truth T2w. VIPP-SR first trains a view-independent patched generator (VIP-GAN) to learn local T1c-to-T2w anatomical correspondence from high-resolution axial slices. The trained generator is then applied to axial, coronal, and sagittal views of the T1c volume to generate three orthogonal T2w estimates. Shape-preserving patching and deepest-skip removal reduce view-specific shortcuts, thereby constraining the generator to learn patch-local representations and enabling the zero-shot inter-plane transfer. Central to VIPP-SR, a projection-based optimization then enforces anatomical consistency across the three view-specific volumes, fusing them by balancing inter-plane self-consistency against per-view data fidelity. The generator is trained on BraTS-MET and evaluated on both the held-out BraTS-MET testing set and the BraTS-GLI cohort without retraining, assessing the cross-cohort generalizability. The results validate that VIPP-SR improves downstream segmentation over the real anisotropic T2w baseline, raising mean-label Dice from 0.330 to 0.465 on BraTS-MET and, zero-shot, from 0.473 to 0.563 on BraTS-GLI and ablation studies identify inter-plane self-consistency as the main source of the gain.

发表机构

• Columbia University（哥伦比亚大学）
• Columbia University Irving Medical Center（哥伦比亚大学欧文医学中心）
• Herbert Irving Comprehensive Cancer Center（赫伯特·欧文综合癌症中心）
• University of Cincinnati（辛辛那提大学）

机构由 AI 辅助整理，请以论文原文为准。