International Journal of Biomedical Imaging / 2013 / Article / Tab 2

Review Article

Computer Aided Diagnostic Support System for Skin Cancer: A Review of Techniques and Algorithms

Table 2

Methods for segmentation of dermoscopic images.

MethodDescriptionRelated references

ThresholdingDetermining threshold and then the pixels are divided into groups based on that criterion. It include bilevel and multithresholdingHistogram thresholding ([90, 91, 109, 110, 223, 224])
Adaptive thresholding ([61, 88, 111, 112, 124, 126, 200, 225])

Color-based segmentation algorithmsSegmentation based on color discrimination. Include principle component transform/spherical coordinate transform[134, 226230]

Discontinuity-based segmentationDetection of lesion edges using active contours/radial search techniques/zero crossing of Laplacian of Gaussian (LoG)Active contours ([58, 62, 64, 88, 231233])
Radial search ([115, 234, 235])
LoG ([117, 163, 236, 237])

Region-based segmentationSplitting the image into smaller components then merging subimages which are adjacent and similar in some sense. It includes Statistical region merging, multiscale region growing, and morphological floodingSplit and merge ([238, 239])
SRM ([59, 70, 92, 112])
Multi-scale ([118, 196])
Morphological flooding ([79])

Soft computingMethods involve the classification of pixels using soft computing techniques including neural networks, fuzzy logic, and evolutionary computationFuzzy logic ([60, 76, 80, 85, 140, 157, 200, 240])
Neural Network ([177, 241])
Optimization algorithms ([241243])

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