Traditionally, radiologists have crudely quantified tumor extent by measuring the longest and shortest dimension by dragging a cursor between opposite boundary points across a single image rather than full segmentation of the volumetric extent. For algorithmic-based volumetric segmentation, the degree of radiologist experiential involvement varies from confirming a fully automated segmentation, to making a single drag on an image to initiate semi-automated segmentation, to making multiple drags and clicks on multiple images during interactive segmentation. An experiment was designed to test an algorithm that allows various levels of interaction. Given the ground-truth of the BraTS training data, which delimits the brain tumors of 285 patients on multi-spectral MR, a computer simulation mimicked the process that a radiologist would follow to perform segmentation with real-time interaction. Clicks and drags were placed only where needed in response to the deviation between real-time segmentation results and assumed radiologist's goal, as provided by the ground-truth. Results of accuracy for various levels of interaction are presented along with estimated elapsed time, in order to measure efficiency. Average total elapsed time, including loading the study through confirming 3D contours, was 46 s.

中文翻译：

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通过模拟用户交互测量半自动脑肿瘤分割的效率

传统上，放射科医生通过在单个图像上的相对边界点之间拖动光标而不是对体积范围进行完全分割来测量最长和最短维度，从而粗略地量化肿瘤范围。对于基于算法的体积分割，放射科医生的经验参与程度从确认全自动分割到在图像上进行一次拖动以启动半自动分割，再到在交互式分割期间多次拖动和点击多个图像。一项实验旨在测试允许各种级别交互的算法。鉴于 BraTS 训练数据的真实性，它在多光谱 MR 上划定了 285 名患者的脑肿瘤，计算机模拟模拟了放射科医生通过实时交互执行分割的过程。仅在需要的地方放置点击和拖动，以响应实时分割结果与假定放射科医师目标之间的偏差，如地面实况提供的那样。各种交互级别的准确性结果与估计的经过时间一起呈现，以衡量效率。平均总经过时间，包括通过确认 3D 轮廓加载研究，为 46 秒。各种交互级别的准确性结果与估计的经过时间一起呈现，以衡量效率。平均总经过时间，包括通过确认 3D 轮廓加载研究，为 46 秒。各种交互级别的准确性结果与估计的经过时间一起呈现，以衡量效率。平均总经过时间，包括通过确认 3D 轮廓加载研究，为 46 秒。