Udupa Jayaram K, Leblanc Vicki R, Zhuge Ying, Imielinska Celina, Schmidt Hilary, Currie Leanne M, Hirsch Bruce E, Woodburn James
Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104-6021, USA.
Comput Med Imaging Graph. 2006 Mar;30(2):75-87. doi: 10.1016/j.compmedimag.2005.12.001.
The purpose of this paper is to describe a framework for evaluating image segmentation algorithms. Image segmentation consists of object recognition and delineation. For evaluating segmentation methods, three factors-precision (reliability), accuracy (validity), and efficiency (viability)-need to be considered for both recognition and delineation. To assess precision, we need to choose a figure of merit, repeat segmentation considering all sources of variation, and determine variations in figure of merit via statistical analysis. It is impossible usually to establish true segmentation. Hence, to assess accuracy, we need to choose a surrogate of true segmentation and proceed as for precision. In determining accuracy, it may be important to consider different 'landmark' areas of the structure to be segmented depending on the application. To assess efficiency, both the computational and the user time required for algorithm training and for algorithm execution should be measured and analyzed. Precision, accuracy, and efficiency factors have an influence on one another. It is difficult to improve one factor without affecting others. Segmentation methods must be compared based on all three factors, as illustrated in an example wherein two methods are compared in a particular application domain. The weight given to each factor depends on application.
本文的目的是描述一个评估图像分割算法的框架。图像分割包括目标识别和轮廓描绘。对于评估分割方法，在识别和描绘方面都需要考虑三个因素——精度（可靠性）、准确性（有效性）和效率（可行性）。为了评估精度，我们需要选择一个品质因数，考虑所有变化源重复进行分割，并通过统计分析确定品质因数的变化。通常不可能建立真正的分割。因此，为了评估准确性，我们需要选择一个真正分割的替代物，并像评估精度一样进行操作。在确定准确性时，根据应用情况考虑要分割结构的不同“地标”区域可能很重要。为了评估效率，应该测量和分析算法训练和算法执行所需的计算时间和用户时间。精度、准确性和效率因素相互影响。很难在不影响其他因素的情况下提高一个因素。分割方法必须基于所有这三个因素进行比较，如在一个特定应用领域中比较两种方法的示例所示。赋予每个因素的权重取决于应用。
