12 May 2004 Delineation operating characteristic (DOC) curve for assessing the accuracy behavior of image segmentation algorithms
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Proceedings Volume 5370, Medical Imaging 2004: Image Processing; (2004); doi: 10.1117/12.535808
Event: Medical Imaging 2004, 2004, San Diego, California, United States
In 2002, at this meeting, we presented a framework for the evaluation of image segmentation methods. That framework suggested the consideration of both recognition and delineation tasks and described three groups of factors under precision, accuracy, and efficiency for evaluating segmentation methods. In this paper, focusing on accuracy, we argue that evaluations conducted on particular manifestations of any segmentation method M (as determined by fixed values of the parameters of M) do not characterize the range of behavior of M. To capture the entire range of behavior of M for a given application domain, we describe a method called Delineation Operating Characteristic (DOC) analysis. The DOC curve summarizes the behavior of M and the tradeoff that is inherent in M between false positive and false negative regions within the regions delineated by M. This, we argue, will allow more complete understanding and more meaningful comparison of the relative accuracy of different methods. This analysis may also allow the selection of more optimal manifestations of M for a given application domain. By way of illustration, we demonstrate with examples how DOC curves can be used for comparing the accuracy of several segmentation methods.
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Jayaram K. Udupa, Ying Zhuge, "Delineation operating characteristic (DOC) curve for assessing the accuracy behavior of image segmentation algorithms", Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); doi: 10.1117/12.535808; https://doi.org/10.1117/12.535808

Image segmentation

Image processing algorithms and systems

Image processing

Fuzzy logic

Binary data


Medical imaging

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