{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,10,22]],"date-time":"2023-10-22T20:45:45Z","timestamp":1698007545112},"reference-count":9,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2007,3,21]],"date-time":"2007-03-21T00:00:00Z","timestamp":1174435200000},"content-version":"vor","delay-in-days":7384,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems &amp; Computers in Japan"],"published-print":{"date-parts":[[1987,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>This paper presents a method of rosette\u2010forming cell classification by image processing. This method is useful in the field of clinical immunology in dividing lymphocytes into some subpopulations and quantifying each component. The \u201cRosette Formation Test\u201d is one of the most popular methods of classifying lymphocytes which consist of the different functional subsets. However, the rosette\u2010nonrosette judgment has been done by a human expert using a microscope. Considerable manpower is needed to judge rosette\/non\u2010rosette cells. To solve this problem, we present a computer classification system of rosette\u2010forming cells in the microscopic image. The system constructs an accumulative gray\u2010level histogram for each cell, extracts features from histograms, and then classifies cells with the discriminant function.<\/jats:p><jats:p>To confirm the effectiveness, we examined the classification system for several images. As a result with learning data (991 cells), the accuracy of classification is 84.5 percent, and the correct rate of resetted and nonrosetted cells is 86.6 percent. With unknown data (509 cells), the accuracy of classification is 84.1 percent, and the correct rate of resetted and nonrosetted cells is 86.2 percent.<\/jats:p>","DOI":"10.1002\/scj.4690180407","type":"journal-article","created":{"date-parts":[[2007,7,7]],"date-time":"2007-07-07T13:33:11Z","timestamp":1183815191000},"page":"64-75","source":"Crossref","is-referenced-by-count":0,"title":["Computer classification of rosette\u2010forming cells from microscope images"],"prefix":"10.1002","volume":"18","author":[{"given":"Hiroki","family":"Ohta","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shinji","family":"Ozawa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minami","family":"Miyauchi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hajime","family":"Takata","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Akira","family":"Sonoda","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hisami","family":"Iri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2007,3,21]]},"reference":[{"key":"e_1_2_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.1972.324072"},{"issue":"4","key":"e_1_2_1_3_2","first-page":"513","article-title":"Leukocyte pattern recognition","volume":"2","author":"Bacus J. W.","year":"1972","journal-title":"I. E. E. E. Trans. SMC"},{"issue":"1","key":"e_1_2_1_4_2","first-page":"54","article-title":"The Classification Procedure for Discriminating between Lymphocytes and Monocytes in the Automatic Identification of White Blood Cells","volume":"59","author":"Ogawa H.","year":"1976","journal-title":"Trans. I. E. C. E."},{"issue":"7","key":"e_1_2_1_5_2","first-page":"499","article-title":"Automatic Classification of White Blood Cells","volume":"60","author":"Nagata Y.","year":"1977","journal-title":"Trans. I. E. C. E."},{"issue":"3","key":"e_1_2_1_6_2","first-page":"227","article-title":"A New Micromethod for Quantification of Human T\u2010 and B\u2010lymphocytes","volume":"43","author":"Tachibana T.","year":"1973","journal-title":"Japan J. Exp. Med."},{"issue":"8","key":"e_1_2_1_7_2","first-page":"763","article-title":"Detection of one method for lymphocyte subpopulations or subsets, a Rosette function test (En, EA, EAC)","volume":"10","author":"Tachibana T.","year":"1982","journal-title":"Medical Technology"},{"key":"e_1_2_1_8_2","first-page":"73","volume-title":"Methods for Statistical Data Analysis of Multivariable Observations","author":"Gnanadesikan R.","year":"1979"},{"key":"e_1_2_1_9_2","article-title":"Computer Classification of Rosette\u2010Forming Cells Using Microscope Images","volume":"24","author":"Yamada M.","year":"1984","journal-title":"I. E. E. E., ISMII'84"},{"key":"e_1_2_1_10_2","volume-title":"Computer Classification of Rosette\u2010Forming Cells Using Microscope Images","author":"Ohta H.","year":"1985"}],"container-title":["Systems and Computers in Japan"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fscj.4690180407","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/scj.4690180407","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,21]],"date-time":"2023-10-21T06:40:11Z","timestamp":1697870411000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/scj.4690180407"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1987,1]]},"references-count":9,"journal-issue":{"issue":"4","published-print":{"date-parts":[[1987,1]]}},"alternative-id":["10.1002\/scj.4690180407"],"URL":"https:\/\/doi.org\/10.1002\/scj.4690180407","archive":["Portico"],"relation":{},"ISSN":["0882-1666","1520-684X"],"issn-type":[{"value":"0882-1666","type":"print"},{"value":"1520-684X","type":"electronic"}],"subject":[],"published":{"date-parts":[[1987,1]]}}}