Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images.
Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images.
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DOI：
10.1016/j.neuroimage.2018.08.003
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发表时间：
2018-12
期刊：
影响因子：
5.7
通讯作者：
Prince JL
中科院分区：
文献类型：
--
作者：
Carass A;Cuzzocreo JL;Han S;Hernandez-Castillo CR;Rasser PE;Ganz M;Beliveau V;Dolz J;Ben Ayed I;Desrosiers C;Thyreau B;Romero JE;Coupé P;Manjón JV;Fonov VS;Collins DL;Ying SH;Onyike CU;Crocetti D;Landman BA;Mostofsky SH;Thompson PM;Prince JL
人类小脑在运动控制、认知功能（即注意力、工作记忆和语言）以及帮助调节情绪反应中起着至关重要的作用。小脑的体内定量评估在包括小脑性共济失调、自闭症和精神分裂症在内的几种神经系统疾病的研究中是重要的。小脑的不同结构细分已被证明与不同的病理相关。为了进一步了解这些病理，以尽可能高的保真度自动包裹小脑是有帮助的。在本文中，我们与世界各地的同事合作，在两个临床队列中评估了自动小脑包裹算法，结果表明，通过更新的方法，小脑包裹可以达到很高的准确性。我们在四个层次上描述这些不同的方法：粗（即整个小脑和总结构），叶，蚓的细分和小叶。由于标签的数量、标签的层次结构、算法的数量和两个队列，我们将分析限制在Dice的重叠度量上。在这种情况下，基于机器学习的方法提供了一系列高效的策略，并在两个队列中提供了高标准的包裹，超越了该领域以前的工作。结合秩和计算，我们确定了一种总体获胜方法。
The human cerebellum plays an essential role in motor control, is involved in cognitive function (i.e., attention, working memory, and language), and helps to regulate emotional responses. Quantitative in-vivo assessment of the cerebellum is important in the study of several neurological diseases including cerebellar ataxia, autism, and schizophrenia. Different structural subdivisions of the cerebellum have been shown to correlate with differing pathologies. To further understand these pathologies, it is helpful to automatically parcellate the cerebellum at the highest fidelity possible. In this paper, we coordinated with colleagues around the world to evaluate automated cerebellum parcellation algorithms on two clinical cohorts showing that the cerebellum can be parcellated to a high accuracy by newer methods. We characterize these various methods at four hierarchical levels: coarse (i.e., whole cerebellum and gross structures), lobe, subdivisions of the vermis, and the lobules. Due to the number of labels, the hierarchy of labels, the number of algorithms, and the two cohorts, we have restricted our analyses to the Dice measure of overlap. Under these conditions, machine learning based methods provide a collection of strategies that are efficient and deliver parcellations of a high standard across both cohorts, surpassing previous work in the area. In conjunction with the rank-sum computation, we identified an overall winning method.
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