Shahedi Maysam, Cool Derek W, Romagnoli Cesare, Bauman Glenn S, Bastian-Jordan Matthew, Rodrigues George, Ahmad Belal, Lock Michael, Fenster Aaron, Ward Aaron D
London Regional Cancer Program, 790 Commissioners Road, London, Ontario N6A 4L6, Canada; University of Western Ontario, Robarts Research Institute, 1151 Richmond Street, London, Ontario N6A 5B7, Canada; University of Western Ontario, Graduate Program in Biomedical Engineering, 1151 Richmond Street, London, Ontario N6A 3K7, Canada.
University of Western Ontario, Robarts Research Institute, 1151 Richmond Street, London, Ontario N6A 5B7, Canada; University of Western Ontario, Department of Medical Imaging, 1151 Richmond Street, London, Ontario N6A 3K7, Canada.
J Med Imaging (Bellingham). 2016 Oct;3(4):046002. doi: 10.1117/1.JMI.3.4.046002. Epub 2016 Nov 7.
Prostate segmentation on T2w MRI is important for several diagnostic and therapeutic procedures for prostate cancer. Manual segmentation is time-consuming, labor-intensive, and subject to high interobserver variability. This study investigated the suitability of computer-assisted segmentation algorithms for clinical translation, based on measurements of interoperator variability and measurements of the editing time required to yield clinically acceptable segmentations. A multioperator pilot study was performed under three pre- and postediting conditions: manual, semiautomatic, and automatic segmentation. We recorded the required editing time for each segmentation and measured the editing magnitude based on five different spatial metrics. We recorded average editing times of 213, 328, and 393 s for manual, semiautomatic, and automatic segmentation respectively, while an average fully manual segmentation time of 564 s was recorded. The reduced measured postediting interoperator variability of semiautomatic and automatic segmentations compared to the manual approach indicates the potential of computer-assisted segmentation for generating a clinically acceptable segmentation faster with higher consistency. The lack of strong correlation between editing time and the values of typically used error metrics ([Formula: see text]) implies that the necessary postsegmentation editing time needs to be measured directly in order to evaluate an algorithm's suitability for clinical translation.
在T2加权磁共振成像（T2w MRI）上进行前列腺分割对于前列腺癌的多种诊断和治疗程序都很重要。手动分割耗时、费力，且观察者间差异较大。本研究基于操作员间差异的测量以及生成临床可接受分割所需的编辑时间测量，探讨了计算机辅助分割算法用于临床转化的适用性。在三种编辑前和编辑后条件下进行了多操作员试点研究：手动、半自动和自动分割。我们记录了每次分割所需的编辑时间，并基于五种不同的空间指标测量了编辑幅度。我们分别记录了手动、半自动和自动分割的平均编辑时间为213秒、328秒和393秒，同时记录的完全手动分割平均时间为564秒。与手动方法相比，半自动和自动分割在编辑后测量的操作员间差异减小，这表明计算机辅助分割有可能以更高的一致性更快地生成临床可接受的分割。编辑时间与通常使用的误差指标值（[公式：见正文]）之间缺乏强相关性，这意味着为了评估算法用于临床转化的适用性，需要直接测量分割后所需的编辑时间。
