{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T00:39:50Z","timestamp":1791419990236,"version":"4.3.3"},"reference-count":21,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2007,3,19]],"date-time":"2007-03-19T00:00:00Z","timestamp":1174262400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Skin Research and Technology"],"published-print":{"date-parts":[[2008,2]]},"abstract":"<jats:p><jats:bold>Background\/purpose: <\/jats:bold> Clinically, it is difficult to differentiate the early stage of malignant melanoma and certain benign skin lesions due to similarity in appearance. Our research uses image analysis of clinical skin images and relative color\u2010based pattern recognition techniques to enhance the images and improve differentiation of these lesions.<\/jats:p><jats:p><jats:bold>Methods: <\/jats:bold> First, the relative color images were created from digitized photographic images. Then, they were segmented into objects and morphologically filtered. Next, the relative color features were extracted from the objects to form two different feature spaces; a lesion feature space and an object feature space. The two feature spaces serve as two data models to be analyzed to determine the best features. Finally, we used a statistical analysis model of relative color features, which better classifies the various types of skin lesions.<\/jats:p><jats:p><jats:bold>Results\/conclusions: <\/jats:bold> The best features found for differentiation of melanoma and benign skin lesions from this study are area, mean in the red and blue bands, standard deviation in the red and green bands, skewness in the green band, and entropy in the red band. With the relative color feature algorithm developed, the best results were obtained with a multi\u2010layer perceptron neural network model. This showed an overall classification success of 79%, with 70% of the benign lesions successfully classified, and 86% of malignant melanoma successfully classified.<\/jats:p>","DOI":"10.1111\/j.1600-0846.2007.00261.x","type":"journal-article","created":{"date-parts":[[2007,3,19]],"date-time":"2007-03-19T17:19:59Z","timestamp":1174324799000},"page":"53-64","source":"Crossref","is-referenced-by-count":87,"title":["Skin lesion classification using relative color features"],"prefix":"10.1111","volume":"14","author":[{"given":"Yue (Iris)","family":"Cheng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ragavendar","family":"Swamisai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Scott E.","family":"Umbaugh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Randy H.","family":"Moss","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"William V.","family":"Stoecker","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saritha","family":"Teegala","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Subhashini K.","family":"Srinivasan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2007,10,18]]},"reference":[{"key":"e_1_2_6_2_2","doi-asserted-by":"publisher","DOI":"10.3322\/canjclin.57.1.43"},{"key":"e_1_2_6_3_2","doi-asserted-by":"publisher","DOI":"10.1046\/j.1525-1500.1998.00052.x"},{"key":"e_1_2_6_4_2","first-page":"1388","article-title":"The performance of solarscan","volume":"141","author":"Menzies SW","year":"2005","journal-title":"an automated dermoscopy image analysis instrument for the diagnosis of primary melanoma"},{"key":"e_1_2_6_5_2","first-page":"573","article-title":"Clinical and dermatoscopic diagnosis of small pigmented skin lesions","volume":"12","author":"Bono A","year":"2002","journal-title":"Eur J Dermatol"},{"key":"e_1_2_6_6_2","doi-asserted-by":"publisher","DOI":"10.1001\/archderm.139.3.361"},{"key":"e_1_2_6_7_2","volume-title":"Computer imaging: digital image analysis and processing","author":"Umbaugh SE.","year":"2005"},{"key":"e_1_2_6_8_2","volume-title":"Partek Tutorials, Version 2.0b","author":"Partek Incorporated","year":"2007"},{"key":"e_1_2_6_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/0895-6111(92)90077-M"},{"key":"e_1_2_6_10_2","unstructured":"LiZ.Development of CVIPtcl\/CVIPwish for graphical user interface Master's project report Southern Illinois University at Edwardsville 1996."},{"key":"e_1_2_6_11_2","unstructured":"McLeanR.Tumor Classification Based on Relative Color Analysis of Melanoma and Non Melanoma Lesion Images MS Thesis Department of Electrical Engineering University of Missouri\u2010Rolla 1994."},{"key":"e_1_2_6_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/51.45955"},{"key":"e_1_2_6_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/51.482850"},{"key":"e_1_2_6_14_2","doi-asserted-by":"publisher","DOI":"10.1109\/51.603650"},{"key":"e_1_2_6_15_2","doi-asserted-by":"publisher","DOI":"10.1201\/9780429258480"},{"key":"e_1_2_6_16_2","volume-title":"Introduction to artificial neural systems","author":"Zurada JM.","year":"1992"},{"key":"e_1_2_6_17_2","volume-title":"Principal component analysis","author":"Jolliffe IT","year":"2002"},{"key":"e_1_2_6_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(05)80056-5"},{"key":"e_1_2_6_19_2","volume-title":"Pattern classification","author":"Duda RO","year":"2000"},{"key":"e_1_2_6_20_2","volume-title":"Neural networks in computer intelligence","author":"LiMin Fu.","year":"1994"},{"key":"e_1_2_6_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/10.312091"},{"key":"e_1_2_6_22_2","first-page":"207","article-title":"Automatic differentiation of melanoma from melanocytic nevi with multispectral digital dermoscopy","volume":"44","author":"Elbaum M","year":"2001","journal-title":"a feasibility study"}],"container-title":["Skin Research and Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1111%2Fj.1600-0846.2007.00261.x","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/j.1600-0846.2007.00261.x","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,10]],"date-time":"2023-10-10T21:24:07Z","timestamp":1696973047000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/j.1600-0846.2007.00261.x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2007,10,18]]},"references-count":21,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2008,2]]}},"alternative-id":["10.1111\/j.1600-0846.2007.00261.x"],"URL":"https:\/\/doi.org\/10.1111\/j.1600-0846.2007.00261.x","archive":["Portico"],"relation":{},"ISSN":["0909-752X","1600-0846"],"issn-type":[{"value":"0909-752X","type":"print"},{"value":"1600-0846","type":"electronic"}],"subject":[],"published":{"date-parts":[[2007,10,18]]}}}