{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T10:52:45Z","timestamp":1776077565917,"version":"3.50.1"},"reference-count":17,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2013,12,12]],"date-time":"2013-12-12T00:00:00Z","timestamp":1386806400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100005710","name":"Universiti Teknologi PETRONAS","doi-asserted-by":"crossref","award":["Internal"],"award-info":[{"award-number":["Internal"]}],"id":[{"id":"10.13039\/501100005710","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Skin Research and Technology"],"published-print":{"date-parts":[[2014,8]]},"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>More than 99% acne patients suffer from acne vulgaris. While diagnosing the severity of acne vulgaris lesions, dermatologists have observed inter\u2010rater and intra\u2010rater variability in diagnosis results. This is because during assessment, identifying lesion types and their counting is a tedious job for dermatologists. To make the assessment job objective and easier for dermatologists, an automated system based on image processing methods is proposed in this study.<\/jats:p><\/jats:sec><jats:sec><jats:title>Objectives<\/jats:title><jats:p>There are two main objectives: (i) to develop an algorithm for the enhancement of various acne vulgaris lesions; and (ii) to develop a method for the segmentation of enhanced acne vulgaris lesions.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>For the first objective, an algorithm is developed based on the theory of high dynamic range (<jats:styled-content style=\"fixed-case\">HDR<\/jats:styled-content>) images. The proposed algorithm uses local rank transform to generate the <jats:styled-content style=\"fixed-case\">HDR<\/jats:styled-content> images from a single acne image followed by the log transformation. Then, segmentation is performed by clustering the pixels based on Mahalanobis distance of each pixel from spectral models of acne vulgaris lesions.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Two metrics are used to evaluate the enhancement of acne vulgaris lesions, i.e., contrast improvement factor (<jats:styled-content style=\"fixed-case\">CIF<\/jats:styled-content>) and image contrast normalization (<jats:styled-content style=\"fixed-case\">ICN<\/jats:styled-content>). The proposed algorithm is compared with two other methods. The proposed enhancement algorithm shows better result than both the other methods based on CIF and ICN. In addition, sensitivity and specificity are calculated for the segmentation results. The proposed segmentation method shows higher sensitivity and specificity than other methods.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>This article specifically discusses the contrast enhancement and segmentation for automated diagnosis system of acne vulgaris lesions. The results are promising that can be used for further classification of acne vulgaris lesions for final grading of the lesions.<\/jats:p><\/jats:sec>","DOI":"10.1111\/srt.12122","type":"journal-article","created":{"date-parts":[[2013,12,12]],"date-time":"2013-12-12T06:22:42Z","timestamp":1386829362000},"page":"322-331","source":"Crossref","is-referenced-by-count":8,"title":["Novel techniques for enhancement and segmentation of acne vulgaris lesions"],"prefix":"10.1111","volume":"20","author":[{"given":"A. S.","family":"Malik","sequence":"first","affiliation":[{"name":"Centre for Intelligent Signal &amp; Imaging Research Universiti Teknologi Petronas Tronoh Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J.","family":"Humayun","sequence":"additional","affiliation":[{"name":"Centre for Intelligent Signal &amp; Imaging Research Universiti Teknologi Petronas Tronoh Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"N.","family":"Kamel","sequence":"additional","affiliation":[{"name":"Centre for Intelligent Signal &amp; Imaging Research Universiti Teknologi Petronas Tronoh Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"F. B.\u2010B.","family":"Yap","sequence":"additional","affiliation":[{"name":"Department of Dermatology Hospital Kuala Lumpur Kuala Lumpur Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2013,12,12]]},"reference":[{"key":"e_1_2_6_2_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1529-8019.2006.00079.x"},{"key":"e_1_2_6_3_1","doi-asserted-by":"publisher","DOI":"10.5021\/ad.2009.21.2.125"},{"key":"e_1_2_6_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1600-0846.2011.00542.x"},{"key":"e_1_2_6_5_1","doi-asserted-by":"publisher","DOI":"10.1046\/j.1365-4362.1997.00099.x"},{"key":"e_1_2_6_6_1","first-page":"1129","article-title":"Phase 4 study to assess tretinoin pump for the treatment of facial acne","volume":"7","author":"Eichenfield LF","year":"2008","journal-title":"J Drugs Dermatol"},{"key":"e_1_2_6_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jaad.2007.06.032"},{"key":"e_1_2_6_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/0190-9622(95)91813-2"},{"key":"e_1_2_6_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0190-9622(97)70070-7"},{"key":"e_1_2_6_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0190-9622(96)90497-1"},{"key":"e_1_2_6_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0190-9622(99)70005-8"},{"key":"e_1_2_6_12_1","first-page":"4078","article-title":"Extraction of acne lesion in acne patients from multispectral images","volume":"2008","author":"Fujii H","journal-title":"Conf Proc IEEE Eng Med Biol Soc"},{"key":"e_1_2_6_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2011.02.005"},{"key":"e_1_2_6_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/258734.258884"},{"key":"e_1_2_6_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/259081.259242"},{"key":"e_1_2_6_16_1","doi-asserted-by":"publisher","DOI":"10.1080\/10867651.1999.10487511"},{"key":"e_1_2_6_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/0034-4257(92)90098-5"},{"key":"e_1_2_6_18_1","volume-title":"Automated early detection of diabetic retinopathy: a semi\u2010supervised approach","author":"Kedir Mohammad ADAL","year":"2012"}],"container-title":["Skin Research and Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1111%2Fsrt.12122","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/srt.12122","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,23]],"date-time":"2023-09-23T13:28:23Z","timestamp":1695475703000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/srt.12122"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,12,12]]},"references-count":17,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2014,8]]}},"alternative-id":["10.1111\/srt.12122"],"URL":"https:\/\/doi.org\/10.1111\/srt.12122","archive":["Portico"],"relation":{},"ISSN":["0909-752X","1600-0846"],"issn-type":[{"value":"0909-752X","type":"print"},{"value":"1600-0846","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,12,12]]}}}