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Separating mixtures of single-fiber orientation distributions for increased sensitivity to crossing white matter fibers

Adam M. Saunders, Gaurav Rudravaram, Michael E. Kim, Elyssa M. McMaster, Yifan Shuai, Warren Boschen, Sophie Lin, Suzana Herculano‐Houzel, Daniel C. Colvin, Yurui Gao, Kurt G. Schilling, Adam W. Anderson, Bennett Landman · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.20974 · cited by 0 works (OpenAlex) · open-access PDF

Chinese

导入:无分散MRI允许在微米尺度上收集的微米级分散,但穿越白质物质纤维增加了在体内传感器数据的探测,例如微结构模型和拖拉图。当前基于固定器的方法来识别脑组织架构的数目,方向和传播纤维依赖于发现纤维方向分布的峰值从受约束的球形分解到白质物质纤维。然而,这种方法是偏向的下游任务的散布,如微结构模型和拖拉图。 方法: 在这项工作中,我们执行一个受约束的非线性优化,称为信号分离分离和迭代的最小千里度估计(FISS)的纤维方向分布。 但是,这种方法被识别为附近纤维

Machine translation (Meta M2M100); the English original follows.

Abstract

Intro: Diffusion MRI allows for in vivo probing of brain tissue architecture via micron-level diffusion aggregated at the millimeter scale, but crossing white matter fibers decrease the sensitivity of downstream tasks such as microstructural modeling and tractography. Current fixel-based methods for identifying the number, orientation, and spread of fibers rely on finding the peaks of fiber orientation distributions from constrained spherical deconvolution. However, this method is biased by the spreads of nearby fibers and fails at angular separations lower than approximately 40-50 degrees. Methods: In this work, we perform a constrained nonlinear optimization called fiber segmentation by signal splitting and iterative least squares estimation (FISSILE), modeling each voxel as a mixture of single-fiber distributions. We use FISSILE to fit axially symmetric fibers in simulations and on three in vivo human subjects from the Human Connectome Project, an ex vivo raccoon brain, as well as the same human subject scanned twice at two different signal-to-noise ratios (SNRs). Results: On simulated data, FISSILE successfully identifies fibers at an angular separation of 40° and a volume fraction of 0.1 at an SNR as low as 30, while MRtrix3's fod2fixel is limited to 60° separation and 0.1 volume fraction at the same SNR. On acquired data, FISSILE identified 85.8% of white matter voxels on average in human brains and 79.4% in the raccoon with at least one fiber crossing, whereas fod2fixel identified 30.1% and 44.5%. The number of white matter fiber crossings was mildly sensitive to different noise levels in the human subject with two acquisitions. Conclusion: A method that models the crossing fiber phenomenon as an unmixing problem increases sensitivity to individual fibers for more precise characterization of anatomy.

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Topics: Voxel, Human Connectome Project, Materials science, Orientation (vector space), Fiber, Sensitivity (control systems)

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