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Publication Detail
Generalised Overlap Measures for Evaluation and Validation in Medical Image Analysis
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Article
  • Authors:
    Crum WR, Camara O, Hill DLG
  • Publisher:
    IEEE
  • Publication date:
    01/11/2006
  • Pagination:
    1451, 1461
  • Journal:
    IEEE Transactions on Medical Imaging
  • Volume:
    25
  • Issue:
    11
  • Print ISSN:
    0278-0062
  • Keywords:
    validation, image registration, overlap
Abstract
Measures of overlap of labelled regions of images, such as the Dice and Tanimoto coefficients, have been extensively used to evaluate image registration and segmentation algorithms. Modern studies can include multiple labels defined on multiple images yet most evaluation schemes report one overlap per labelled region, simply averaged over multiple images. In this paper common overlap measures are generalised to measure the total overlap of ensembles of labels defined on multiple test images and account for fractional labels using fuzzy set theory. This framework allows a single “figure-of-merit” to be reported which summarises the results of a complex experiment by image pair, by label or overall. A complementary measure of error, the Overlap Distance (OD), is defined which captures the spatial extent of the non-overlapping part and is related to the Hausdorff Distance computed on grey level images. The generalised overlap measures are validated on synthetic images for which the overlap can be computed analytically and used as similarity measures in non-rigid registration of 3D MRI brain images. Finally a pragmatic segmentation ground truth is constructed by registering an MR atlas brain to twenty individual scans, and used with the overlap measures to evaluate the publicly available brain segmentation algorithms.
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