{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T15:14:32Z","timestamp":1790694872734,"version":"4.1.0"},"reference-count":28,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2017,7,20]],"date-time":"2017-07-20T00:00:00Z","timestamp":1500508800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"name":"Agilent Technologies, Inc. Research Project Grant","award":["ACT-UR #3898."],"award-info":[{"award-number":["ACT-UR #3898."]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cytometry Pt A"],"published-print":{"date-parts":[[2017,8]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Currently, diagnosis of colon cancer is based on manual examination of histopathological images by a pathologist. This can be time consuming and interpretation of the images is subject to inter\u2010 and intra\u2010observer variability. This may be improved by introducing a computer\u2010aided diagnosis (CAD) system for automatic detection of cancer tissue within whole slide hematoxylin and eosin (H&amp;E) stains. Cancer disrupts the normal control mechanisms of cell proliferation and differentiation, affecting the structure and appearance of the cells. Therefore, extracting features from segmented cell nuclei structures may provide useful information to detect cancer tissue. A framework for automatic classification of regions of interest (ROI) containing either benign or cancerous colon tissue extracted from whole slide H&amp;E stained images using cell nuclei features was proposed. A total of 1,596 ROI's were extracted from 87 whole slide H&amp;E stains (44 benign and 43 cancer). A cell nuclei segmentation algorithm consisting of color deconvolution, k\u2010means clustering, local adaptive thresholding, and cell separation was performed within the ROI's to extract cell nuclei features. From the segmented cell nuclei structures a total of 750 texture and intensity\u2010based features were extracted for classification of the ROI's. The nine most discriminative cell nuclei features were used in a random forest classifier to determine if the ROI's contained benign or cancer tissue. The ROI classification obtained an area under the curve (AUC) of 0.96, sensitivity of 0.88, specificity of 0.92, and accuracy of 0.91 using an optimized threshold. The developed framework showed promising results in using cell nuclei features to classify ROIs into containing benign or cancer tissue in H&amp;E stained tissue samples. \u00a9 2017 International Society for Advancement of Cytometry<\/jats:p>","DOI":"10.1002\/cyto.a.23175","type":"journal-article","created":{"date-parts":[[2017,7,20]],"date-time":"2017-07-20T15:27:31Z","timestamp":1500564451000},"page":"785-793","source":"Crossref","is-referenced-by-count":44,"title":["Using cell nuclei features to detect colon cancer tissue in hematoxylin and eosin stained slides"],"prefix":"10.1002","volume":"91","author":[{"given":"Alex Skovsbo","family":"J\u00f8rgensen","sequence":"first","affiliation":[{"name":"Department of Health Science and Technology Aalborg University Aalborg Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anders Munk","family":"Rasmussen","sequence":"additional","affiliation":[{"name":"Department of Health Science and Technology Aalborg University Aalborg Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Niels Kristian M\u00e4kinen","family":"Andersen","sequence":"additional","affiliation":[{"name":"Department of Health Science and Technology Aalborg University Aalborg Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simon Kragh","family":"Andersen","sequence":"additional","affiliation":[{"name":"Department of Health Science and Technology Aalborg University Aalborg Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonas","family":"Emborg","sequence":"additional","affiliation":[{"name":"Diagnostics &amp; Genomics Group, Dako Denmark A\/S An Agilent Technologies Company Glostrup Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rasmus","family":"R\u00f8ge","sequence":"additional","affiliation":[{"name":"Institute of Pathology, Aalborg University Hospital, Denmark and the Department of Clinical Medicine, Aalborg University Aalborg Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lasse Riis","family":"\u00d8stergaard","sequence":"additional","affiliation":[{"name":"Department of Health Science and Technology Aalborg University Aalborg Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2017,7,20]]},"reference":[{"key":"e_1_2_6_2_1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21220"},{"key":"e_1_2_6_3_1","doi-asserted-by":"publisher","DOI":"10.1055\/s-0029-1242458"},{"key":"e_1_2_6_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/ijc.29210"},{"key":"e_1_2_6_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/RBME.2009.2034865"},{"key":"e_1_2_6_6_1","doi-asserted-by":"publisher","DOI":"10.1136\/jcp.48.9.856"},{"key":"e_1_2_6_7_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.298.6675.707"},{"key":"e_1_2_6_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/RBME.2013.2295804"},{"key":"e_1_2_6_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITB.2008.2009441"},{"key":"e_1_2_6_10_1","doi-asserted-by":"crossref","first-page":"4844","DOI":"10.1109\/IEMBS.2006.260837","article-title":"Image analysis for neuroblastoma classification: Segmentation of cell nuclei","volume":"1","author":"Gurcan MN","year":"2006","journal-title":"Conf Proc IEEE Eng Med Biol Soc"},{"key":"e_1_2_6_11_1","doi-asserted-by":"publisher","DOI":"10.1038\/srep00503"},{"key":"e_1_2_6_12_1","first-page":"504","article-title":"A boosting cascade for automated detection of prostate cancer from digitized histology","volume":"2006","author":"Doyle S","year":"2006","journal-title":"Med Image Comput Comput Interv"},{"key":"e_1_2_6_13_1","doi-asserted-by":"publisher","DOI":"10.1080\/14639230500077444"},{"key":"e_1_2_6_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2010.01.005"},{"key":"e_1_2_6_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2011.2141674"},{"key":"e_1_2_6_16_1","first-page":"291","article-title":"Quantification of histochemical staining by color deconvolution","volume":"23","author":"Ruifrok A","year":"2001","journal-title":"Anal Quant Cytol Histol"},{"key":"e_1_2_6_17_1","first-page":"1729","article-title":"An efficient technique for nuclei segmentation in histopathological images based on morphological reconstructions and region adaptive threshold","volume":"18","author":"Xu H","year":"2014","journal-title":"Pattern Recognit Lett"},{"key":"e_1_2_6_18_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0070221"},{"key":"e_1_2_6_19_1","doi-asserted-by":"crossref","unstructured":"ZhangT BaiX SongX NiuX.An improved algorithm for multiple closed contour detection. 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