An improved objective evaluation measure for border detection in dermoscopy images.
BACKGROUND
Dermoscopy is one of the major imaging modalities used in the diagnosis of melanoma and other pigmented skin lesions. Owing to the difficulty and subjectivity of human interpretation, dermoscopy image analysis has become an important research area. One of the most important steps in dermoscopy image analysis is the automated detection of lesion borders. Although numerous methods have been developed for the detection of lesion borders, very few studies were comprehensive in the evaluation of their results.


METHODS
In this paper, we evaluate five recent border detection methods on a set of 90 dermoscopy images using three sets of dermatologist-drawn borders as the ground truth. In contrast to previous work, we utilize an objective measure, the normalized probabilistic rand index, which takes into account the variations in the ground-truth images.


CONCLUSIONS
The results demonstrate that the differences between four of the evaluated border detection methods are in fact smaller than those predicted by the commonly used exclusive-OR measure.
Celebi
M Emre
ME
Department of Computer Science, Louisiana State University, Shreveport, LA, USA.
Schaefer
Gerald
G
Iyatomi
Hitoshi
H
Stoecker
William V
WV
Malters
Joseph M
JM
Grichnik
James M
JM
D046169:Dermoscopy / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008545:Melanoma / Q000473:pathology*; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D012680:Sensitivity and Specificity; D012867:Skin / Q000473:pathology*; D012878:Skin Neoplasms / Q000473:pathology*