Variability in human and automatic segmentation of melanocytic lesions
In a double blind evaluation of 60 digital dermatoscopic images by 4 ldquojuniorrdquo, 4 ldquoseniorrdquo and 4 ldquoexpertrdquo dermatologists (dermatoscopy training respectively less than 1 year, between 1 and 5 years, and more than 5 years), a significant inter-operator variability was observed i...
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Published in | 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society Vol. 2009; pp. 5789 - 5792 |
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Main Authors | , , , , , |
Format | Conference Proceeding Journal Article |
Language | English |
Published |
United States
IEEE
01.01.2009
|
Subjects | |
Online Access | Get full text |
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Summary: | In a double blind evaluation of 60 digital dermatoscopic images by 4 ldquojuniorrdquo, 4 ldquoseniorrdquo and 4 ldquoexpertrdquo dermatologists (dermatoscopy training respectively less than 1 year, between 1 and 5 years, and more than 5 years), a significant inter-operator variability was observed in melanocytic lesion border identification (with a disagreement of the order of 10 - 20% of the area of the lesions). Expert dermatologists showed greater agreement among themselves than with senior and junior dermatologists, and a slight tendency towards ldquotighterrdquo segmentations. The human inter-operator variability was then used to evaluate the segmentation accuracy of 4 algorithms, representative of the 3 fundamental state-of-the-art automated segmentation techniques and of a fourth, novel, technique. Our evaluation methodology addresses a number of crucial difficulties encountered in previous studies and may be of independent interest. 3 of the 4 algorithms showed considerably less agreement with expert dermatologists than even senior and junior dermatologists did (with a disagreement of the order of 30% of the area of the lesions); the remaining algorithm, however, showed agreement with expert dermatologists comparable to that of other expert dermatologists. |
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ISSN: | 1094-687X 1557-170X 1558-4615 |
DOI: | 10.1109/IEMBS.2009.5332543 |