1. Enhancing classification accuracy utilizing globules and dots features in digital dermoscopy 
Ilias Maglogiannis, Konstantinos K. Delibasis 
Computer Methods and Programs in Biomedicine 
Volume 118, Issue 2, Pages (February 2015)
DOI: /j.cmpb
Copyright © 2014 Elsevier Ireland Ltd Terms and Conditions

2. Fig. 1 The graphical outline of the algorithm.
Computer Methods and Programs in Biomedicine  , DOI: ( /j.cmpb )
Copyright © 2014 Elsevier Ireland Ltd Terms and Conditions

3. Fig. 2
The measure of circularity fσ (λ1,λ2) of Eq. (11) for different values of the two eigenvalues of the Hessian matrix in Eq. (8).
Computer Methods and Programs in Biomedicine  , DOI: ( /j.cmpb )
Copyright © 2014 Elsevier Ireland Ltd Terms and Conditions

4. Fig. 3
A part of a dermoscopy image enhanced by the inverse non-linear diffusion at 20, 40, 60, 80 and 100 iteration (lines 2–6 respectively), with δt=0.1, using σ equal 1, 2 and 3 (columns 1–3 respectively).
Computer Methods and Programs in Biomedicine  , DOI: ( /j.cmpb )
Copyright © 2014 Elsevier Ireland Ltd Terms and Conditions

5. Fig. 4
The intermediate steps of dot segmentation for an exemplar dermoscopy image.
Computer Methods and Programs in Biomedicine  , DOI: ( /j.cmpb )
Copyright © 2014 Elsevier Ireland Ltd Terms and Conditions

6. Fig. 5
Examples dot segmentation and lesion feature extraction of malignant melanoma (rows 1 and 2) and benign skin lesions (rows 3–5). In the left column, the segmented dots are superimposed on the original dermoscopy images. In the right column, the centers of mass of the segmented dots are shown on the original image, as well, as the with the center of mass of the segmented dark dots superimposed, along with the primary symmetry axis and the manually delineated boundary of the skin lesion.
Computer Methods and Programs in Biomedicine  , DOI: ( /j.cmpb )
Copyright © 2014 Elsevier Ireland Ltd Terms and Conditions