Evaluation of Segmentation algorithms for Medical Imaging.
This paper describes an approach to be used for medical image segmentation evaluation. The process for segmenting organs and structures from medical images is gaining increased importance in the diagnosis of diseases and in guiding minimally invasive surgical and therapeutic procedures. While investigators are continuing to develop novel new segmentation approaches, little attention has been given to the development of a uniform and common framework for and performance metrics to be used in comparing different algorithms, in optimizing algorithms and in evaluating their performance. Choosing an appropriate effectiveness measure of object segmentation is a difficult task and weighting the importance of different possible performance metrics requires matching the metrics to the segmentation objectives. However, in all tasks, it is now believed that three types of metrics must be measured and reported: accuracy, precision and efficiency. In this paper, we review some of these metrics.
Fenster
Aaron
A
director of the Imaging Research Laboratories, Robarts Research Institute, London, Ontario N6A 5K8, Canada (Phone:
Chiu
Bernard
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