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PROSTATEx Challenges for computerized classification of prostate lesions from multiparametric magnetic resonance images

机译:从多参数磁共振图像对前列腺病变进行计算机分类的PROSTATEx挑战

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摘要

Grand challenges stimulate advances within the medical imaging research community; within a competitive yet friendly environment, they allow for a direct comparison of algorithms through a well-defined, centralized infrastructure. The tasks of the two-part PROSTATEx Challenges (the PROSTATEx Challenge and the PROSTATEx-2 Challenge) are (1) the computerized classification of clinically significant prostate lesions and (2) the computerized determination of Gleason Grade Group in prostate cancer, both based on multiparametric magnetic resonance images. The challenges incorporate well-vetted cases for training and testing, a centralized performance assessment process to evaluate results, and an established infrastructure for case dissemination, communication, and result submission. In the PROSTATEx Challenge, 32 groups apply their computerized methods (71 methods total) to 208 prostate lesions in the test set. The area under the receiver operating characteristic curve for these methods in the task of differentiating between lesions that are and are not clinically significant ranged from 0.45 to 0.87; statistically significant differences in performance among the top-performing methods, however, are not observed. In the PROSTATEx-2 Challenge, 21 groups apply their computerized methods (43 methods total) to 70 prostate lesions in the test set. When compared with the reference standard, the quadratic-weighted kappa values for these methods in the task of assigning a five-point Gleason Grade Group to each lesion range from to 0.27; superiority to random guessing can be established for only two methods. When approached with a sense of commitment and scientific rigor, challenges foster interest in the designated task and encourage innovation in the field.
机译:巨大的挑战激发了医学影像研究界的进步;在竞争激烈但友好的环境中,它们允许通过定义明确的集中式基础结构直接比较算法。分为两部分的PROSTATEx挑战(PROSTATEx挑战和PROSTATEx-2挑战)的任务是(1)对临床上重要的前列腺病变进行计算机分类,以及(2)对前列腺癌的Gleason分级组进行计算机确定,两者均基于多参数磁共振图像。这些挑战包括经过良好审查的培训和测试案例,用于评估结果的集中绩效评估流程以及用于案例传播,沟通和结果提交的已建立基础设施。在PROSTATEx挑战赛中,有32个小组将其计算机化方法(共71种方法)应用于测试集中的208个前列腺病变。这些方法在区分临床上和非临床上显着的病灶时,接收器工作特征曲线下的面积为0.45至0.87;但是,未观察到性能最高的方法之间在统计上的显着差异。在PROSTATEx-2挑战中,有21个小组将其计算机化方法(总共43种方法)应用于测试集中的70个前列腺病变。与参考标准相比,这些方法的二次加权kappa值是为每个病变分配五点格里森等级组的任务,范围从到0.27;只有两种方法才能建立优于随机猜测的优势。勇于承担并具有科学严谨性时,挑战会激发对指定任务的兴趣并鼓励该领域的创新。

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