AI Article Synopsis
- Segmentation is crucial for accurately identifying pigmented skin lesions in computer-aided diagnostics, as clearly defining the lesion boundaries helps differentiate benign from malignant cases.
- The paper introduces a novel segmentation approach that combines Independent Component Analysis to locate skin lesions, followed by a refinement using a Level-set method.
- The proposed method was tested on 141 images and demonstrated a segmentation error of 16.55%, outperforming other leading techniques in the literature.
Article Abstract
Segmentation is an important step in computer-aided diagnostic systems for pigmented skin lesions, since that a good definition of the lesion area and its boundary at the image is very important to distinguish benign from malignant cases. In this paper a new skin lesion segmentation method is proposed. This method uses Independent Component Analysis to locate skin lesions in the image, and this location information is further refined by a Level-set segmentation method. Our method was evaluated in 141 images and achieved an average segmentation error of 16.55%, lower than the results for comparable state-of-the-art methods proposed in literature.
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| http://dx.doi.org/10.1109/IEMBS.2011.6091481 | DOI Listing |
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