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The four stages of melanoma progression were represented by seven tissue types, including benign nevus, primary tumors with radial and vertical growth patterns (stage I) and four secondary metastatic tumors: subcutaneous (stage II), lymph node (stage III), gastrointestinal and soft tissue (stage IV). Our experiment setup comprised 14,208 image samples based on 164 TMA cores. In our experiments, we constructed an HE color space by digitally deconvolving the RGB images into separate H (hematoxylin) and E (eosin) channels. We also compared three different classifiers: Weighted Neighbor Distance (WND), Radial Basis Functions (RBF), and k\u2010Nearest Neighbors (kNN). We found that the HE color space consistently outperformed other color spaces with all three classifiers, while the different classifiers did not have as large of an effect on accuracy. This showed that a more physiologically relevant representation of color can have a larger effect on correct image interpretation than downstream processing steps. We were able to correctly classify individual fields of view with an average of 96% accuracy when randomly splitting the dataset into training and test fields. We also obtained a classification accuracy of 100% when testing entire cores that were not previously used in training (four random trials with one test core for each of 7 classes, 28 tests total). Because each core corresponded to a different patient, this test more closely mimics a clinically relevant setting where new patients are evaluated based on training with previous cases. The analysis method used in this study contains no parameters or adjustments that are specific to melanoma morphology, suggesting it can be used for analyzing other tissues and phenotypes, as well as potentially different image modalities and contrast techniques. Published 2012 Wiley Periodicals, Inc.<\/jats:p>","DOI":"10.1002\/cyto.a.22044","type":"journal-article","created":{"date-parts":[[2012,4,2]],"date-time":"2012-04-02T13:56:57Z","timestamp":1333375017000},"page":"364-373","source":"Crossref","is-referenced-by-count":8,"title":["Automatic detection of melanoma progression by histological analysis of secondary sites"],"prefix":"10.1002","volume":"81A","author":[{"given":"Nikita V.","family":"Orlov","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ashani T.","family":"Weeraratna","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stephen M.","family":"Hewitt","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christopher E.","family":"Coletta","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John D.","family":"Delaney","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"D.","family":"Mark Eckley","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lior","family":"Shamir","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ilya G.","family":"Goldberg","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2012,3,29]]},"reference":[{"key":"e_1_2_8_2_2","first-page":"705","article-title":"The histogenesis and biologic behavior of primary human malignant melanomas of the skin","volume":"29","author":"Clark JWH","year":"1969","journal-title":"Cancer Res"},{"key":"e_1_2_8_3_2","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordjournals.bmb.a072979"},{"key":"e_1_2_8_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2006.09.041"},{"key":"e_1_2_8_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TITB.2009.2020159"},{"key":"e_1_2_8_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2011.2128870"},{"key":"e_1_2_8_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2011.2110648"},{"key":"e_1_2_8_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/TITB.2006.888703"},{"key":"e_1_2_8_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2007.898536"},{"key":"e_1_2_8_10_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2009.2012704"},{"key":"e_1_2_8_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/TITB.2006.879596"},{"key":"e_1_2_8_12_2","first-page":"254","article-title":"Computer\u2010aided classification of centroblast cells in follicular lymphoma","volume":"32","author":"Belkacem\u2010Boussaid K","year":"2010","journal-title":"Anal Quant Cytol Histol"},{"key":"e_1_2_8_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2009.2035305"},{"key":"e_1_2_8_14_2","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2010.2041232"},{"key":"e_1_2_8_15_2","first-page":"1","article-title":"A boosted bayesian multi\u2010resolution classifier for prostate cancer detection from digitized needle biopsies","volume":"57","author":"Doyle S","year":"2010","journal-title":"IEEE Trans Biomed Eng"},{"key":"e_1_2_8_16_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-007-0066-x"},{"key":"e_1_2_8_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2007.09.005"},{"key":"e_1_2_8_18_2","volume-title":"Using 3D information for classification of non\u2010melanoma skin lesions","author":"McDonagh S","year":"2008"},{"key":"e_1_2_8_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/42.918473"},{"key":"e_1_2_8_20_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1600-0846.2008.00303.x"},{"key":"e_1_2_8_21_2","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1055\/s-0038-1634144","article-title":"Computer\u2010supported diagnosis of melanoma in profilometry","volume":"38","author":"Handels H","year":"1999","journal-title":"Methods Inform Med"},{"key":"e_1_2_8_22_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1600-0846.2007.00261.x"},{"key":"e_1_2_8_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/S1386-5056(02)00049-7"},{"key":"e_1_2_8_24_2","doi-asserted-by":"publisher","DOI":"10.1038\/jid.2008.28"},{"key":"e_1_2_8_25_2","doi-asserted-by":"publisher","DOI":"10.1007\/s001380050104"},{"key":"e_1_2_8_26_2","doi-asserted-by":"publisher","DOI":"10.1109\/TITB.2008.2008801"},{"key":"e_1_2_8_27_2","doi-asserted-by":"crossref","unstructured":"MasoodK RajpootN.Texture based classification of hyperspectral colon biopsy samples using CBLP. 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