论文标题
使用426例病例对三种自动分割的三种自动分割方法的比较评估
Comparative Evaluation Of Three Methods Of Automatic Segmentation Of Brain Structures Using 426 Cases
论文作者
论文摘要
大型磁共振图像（MRI）中大脑结构的分割需要自动分割而不是手动跟踪。自动分割方法为手动分割提供了急需的替代方法，既是劳动密集型又耗时。在大脑结构中，海马由于形状不规则，尺寸小和不明确的边缘而提出了一项具有挑战性的分割任务。在这项工作中，我们使用426名受试者的T1加权MRI来验证该方法并比较三种自动分割方法：Freesurfer，localinfo和ABS。使用四项评估措施来评估海马自动分割和手动分割之间的一致性。 ABS根据骰子系数，精度，Hausdorff距离，ASSD，RMS，相似性，敏感性和体积一致性胜过其他人。此外，使用1.5T和3T MRI系统获得的分割结果的比较表明，ABS对3T MRI的现场不均匀性更敏感。
Segmentation of brain structures in a large dataset of magnetic resonance images (MRI) necessitates automatic segmentation instead of manual tracing. Automatic segmentation methods provide a much-needed alternative to manual segmentation which is both labor intensive and time-consuming. Among brain structures, the hippocampus presents a challenging segmentation task due to its irregular shape, small size, and unclear edges. In this work, we use T1-weighted MRI of 426 subjects to validate the approach and compare three automatic segmentation methods: FreeSurfer, LocalInfo, and ABSS. Four evaluation measures are used to assess agreement between automatic and manual segmentation of the hippocampus. ABSS outperformed the others based on the Dice coefficient, precision, Hausdorff distance, ASSD, RMS, similarity, sensitivity, and volume agreement. Moreover, comparison of the segmentation results, acquired using 1.5T and 3T MRI systems, showed that ABSS is more sensitive than the others to the field inhomogeneity of 3T MRI.
