Abstract:
BACKGROUND:Given its propensity to metastasize, and lack of effective therapies for most patients with advanced disease, early detection of melanoma is a clinical imperative. Different computer-aided diagnosis (CAD) systems have been proposed to increase the specificity and sensitivity of melanoma detection. Although such computer programs are developed for different diagnostic algorithms, to the best of our knowledge, a system to classify different melanocytic lesions has not been proposed yet. METHOD:In this research we present a new approach to the classification of melanocytic lesions. This work is focused not only on categorization of skin lesions as benign or malignant but also on specifying the exact type of a skin lesion including melanoma, Clark nevus, Spitz/Reed nevus, and blue nevus. The proposed automatic algorithm contains the following steps: image enhancement, lesion segmentation, feature extraction, and selection as well as classification. RESULTS:The algorithm has been tested on 300 dermoscopic images and achieved accuracy of 92% indicating that the proposed approach classified most of the melanocytic lesions correctly. CONCLUSIONS:A proposed system can not only help to precisely diagnose the type of the skin mole but also decrease the amount of biopsies and reduce the morbidity related to skin lesion excision.
journal_name
Biomed Res Intjournal_title
BioMed research internationalauthors
Jaworek-Korjakowska J,Kłeczek Pdoi
10.1155/2016/8934242subject
Has Abstractpub_date
2016-01-01 00:00:00pages
8934242eissn
2314-6133issn
2314-6141journal_volume
2016pub_type
杂志文章abstract::[This corrects the article DOI: 10.1155/2013/783690.]. ...
journal_title:BioMed research international
pub_type: 已发布勘误
doi:10.1155/2016/8693826
更新日期:2016-01-01 00:00:00
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journal_title:BioMed research international
pub_type: 杂志文章,meta分析,评审
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journal_title:BioMed research international
pub_type: 杂志文章,随机对照试验
doi:10.1155/2015/240506
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journal_title:BioMed research international
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journal_title:BioMed research international
pub_type: 杂志文章
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pub_type: 临床试验,杂志文章
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journal_title:BioMed research international
pub_type: 杂志文章,评审
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journal_title:BioMed research international
pub_type: 杂志文章
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journal_title:BioMed research international
pub_type: 杂志文章,评审
doi:10.1155/2014/784706
更新日期:2014-01-01 00:00:00
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journal_title:BioMed research international
pub_type: 杂志文章,评审
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journal_title:BioMed research international
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doi:10.1155/2016/1893474
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pub_type: 杂志文章
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journal_title:BioMed research international
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doi:10.1155/2014/578698
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journal_title:BioMed research international
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journal_title:BioMed research international
pub_type: 杂志文章
doi:10.1155/2020/8863737
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journal_title:BioMed research international
pub_type: 杂志文章
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journal_title:BioMed research international
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journal_title:BioMed research international
pub_type: 杂志文章
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journal_title:BioMed research international
pub_type: 杂志文章
doi:10.1155/2018/2961767
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journal_title:BioMed research international
pub_type: 杂志文章,meta分析
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journal_title:BioMed research international
pub_type: 杂志文章
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journal_title:BioMed research international
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