Literature DB >> 22255705

An ICA-based method for the segmentation of pigmented skin lesions in macroscopic images.

Pablo G Cavalcanti1, Jacob Scharcanski, Leandro E Di Persia, Diego H Milone.   

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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Year:  2011        PMID: 22255705     DOI: 10.1109/IEMBS.2011.6091481

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  Segmentation and classification of consumer-grade and dermoscopic skin cancer images using hybrid textural analysis.

Authors:  Afsah Saleem; Naeem Bhatti; Aqueel Ashraf; Muhammad Zia; Hasan Mehmood
Journal:  J Med Imaging (Bellingham)       Date:  2019-08-06

2.  Automatic skin lesion segmentation by coupling deep fully convolutional networks and shallow network with textons.

Authors:  Lei Zhang; Guang Yang; Xujiong Ye
Journal:  J Med Imaging (Bellingham)       Date:  2019-04-15
  2 in total

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