White matter fiber clustering (WMFC) parcellates tractography data into anatomically meaningful fiber bundles, usually in an unsupervised manner without the need of labeled ground truth data. While widely used WMFC approaches have shown good performance using classical machine learning techniques, recent advances in deep learning reveal a promising direction towards fast and effective WMFC. In this work, we propose a novel deep learning framework for WMFC, Deep Fiber Clustering (DFC), which solves the unsupervised clustering problem as a self-supervised learning task with a domain-specific pretext task to predict pairwise fiber distances. This accelerates the fiber representation learning to handle a known challenge in WMFC, i.e., the sensitivity of clustering results to the point ordering along fibers. We design a novel network architecture that represents input fibers as point clouds and allows the incorporation of additional sources of input information from gray matter parcellation. Thus DFC makes use of the combined white matter fiber geometry and gray matter anatomical parcellation to improve anatomical coherence of fiber clusters. In addition, DFC conducts outlier removal in a natural way by rejecting fibers with low cluster assignment probabilities. We evaluate DFC on three independently acquired cohorts (including data from 220 subjects) and compare it to several state-of-the-art WMFC algorithms. Experimental results demonstrate superior performance of DFC in terms of cluster compactness, generalization ability, anatomical coherence, and computational efficiency. In addition, DFC parcellates whole brain tractography with 50k fibers in about 1.5 minutes, providing a fast and efficient tool for large data analysis.
翻译:白物纤维聚集(WMFC) 包状成份色色色色色色色素数据,通常在不需要贴标签的地面真实数据的情况下,以不受监督的方式,以不受监督的方式,将毛质成解剖纤维包件。虽然广泛使用的纤维代表制方法使用古典机器学习技术表现出了良好的表现,但最近深层学习的进展揭示了快速和有效WMFCC的一个有希望的方向。在这项工作中,我们为WMFC、深纤维聚集(DFC)提出了一个全新的深层次学习框架,解决了未经监督的组群问题,将其作为一种自我监督的骨质化骨质化的骨质化骨质化任务,以预测双纤维纤维距离的距离。此外,DFC在WMCC中,即集成结果的敏感度和直径直径直到纤维的点。我们设计了一个新的网络结构结构,将输入纤维纤维的纤维的纤维化(DFC) 和直径直径直的直径直径直径直径直径直径直径直径直径直径直径直径直径直径直径直径直径直径直径直径直径直分析。