dc.creator | Maglogiannis, I. | en |
dc.creator | Delibasis, K. K. | en |
dc.date.accessioned | 2015-11-23T10:38:21Z | |
dc.date.available | 2015-11-23T10:38:21Z | |
dc.date.issued | 2015 | |
dc.identifier | 10.1016/j.cmpb.2014.12.001 | |
dc.identifier.issn | 0169-2607 | |
dc.identifier.uri | http://hdl.handle.net/11615/30488 | |
dc.description.abstract | The interest in image dermoscopy has been significantly increased recently and skin lesion images are nowadays routinely acquired for a number of skin disorders. An important finding in the assessment of a skin lesion severity is the existence of dark dots and globules, which are hard to locate and count using existing image software tools. In this work we present a novel methodology for detecting/segmenting and count dark dots and globules from dermoscopy images. Segmentation is performed using a multi-resolution approach based on inverse non-linear diffusion. Subsequently, a number of features are extracted from the segmented dots/globules and their diagnostic value in automatic classification of dermoscopy images of skin lesions into melanoma and non-malignant nevus is evaluated. The proposed algorithm is applied to a number of images with skin lesions with known histo-pathology. Results show that the proposed algorithm is very effective in automatically segmenting dark dots and globules. Furthermore, it was found that the features extracted from the segmented dots/globules can enhance the performance of classification algorithms that discriminate between malignant and benign skin lesions, when they are combined with other region-based descriptors. (C) 2014 Elsevier Ireland Ltd. All rights reserved. | en |
dc.source.uri | <Go to ISI>://WOS:000348045000003 | |
dc.subject | Dermoscopy images | en |
dc.subject | Skin lesions | en |
dc.subject | Dark dot segmentation | en |
dc.subject | Globule | en |
dc.subject | segmentation | en |
dc.subject | Image classification | en |
dc.subject | Melanoma detection | en |
dc.subject | MELANOCYTIC SKIN-LESIONS | en |
dc.subject | ANISOTROPIC DIFFUSION | en |
dc.subject | IMAGE-ANALYSIS | en |
dc.subject | DIAGNOSIS | en |
dc.subject | MELANOMA | en |
dc.subject | SCHEME | en |
dc.subject | SYSTEM | en |
dc.subject | BORDER | en |
dc.subject | SCALE | en |
dc.subject | Computer Science, Interdisciplinary Applications | en |
dc.subject | Computer Science, | en |
dc.subject | Theory & Methods | en |
dc.subject | Engineering, Biomedical | en |
dc.subject | Medical Informatics | en |
dc.title | Enhancing classification accuracy utilizing globules and dots features in digital dermoscopy | en |
dc.type | journalArticle | en |