{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,5]],"date-time":"2025-10-05T19:59:54Z","timestamp":1759694394738,"version":"3.37.3"},"reference-count":32,"publisher":"Wiley","license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Computational Intelligence and Soft Computing"],"published-print":{"date-parts":[[2017]]},"abstract":"<jats:p>This paper presents a two-dimensional wavelet based decomposition algorithm for classification of biomedical images. The two-dimensional wavelet decomposition is done up to five levels for the input images. Histograms of decomposed images are then used to form the feature set. This feature set is further reduced using probabilistic principal component analysis. The reduced set of features is then fed into either <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M1\"><mml:mrow><mml:mi>K<\/mml:mi><\/mml:mrow><\/mml:math> nearest neighbor algorithm or feed-forward artificial neural network, to classify images. The algorithm is compared with three other techniques in terms of accuracy. The proposed algorithm has been found better up to 3.3%, 12.75%, and 13.75% on average over the first, second, and third algorithm, respectively, using KNN and up to 6.22%, 13.9%, and 14.1% on average using ANN. The dataset used for comparison consisted of CT Scan images of lungs and MR images of heart as obtained from different sources.<\/jats:p>","DOI":"10.1155\/2017\/9571262","type":"journal-article","created":{"date-parts":[[2017,12,24]],"date-time":"2017-12-24T18:30:49Z","timestamp":1514140249000},"page":"1-9","source":"Crossref","is-referenced-by-count":15,"title":["A Five-Level Wavelet Decomposition and Dimensional Reduction Approach for Feature Extraction and Classification of MR and CT Scan Images"],"prefix":"10.1155","volume":"2017","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4695-8575","authenticated-orcid":true,"given":"Varun","family":"Srivastava","sequence":"first","affiliation":[{"name":"University School of Information and Communication Technology, Guru Gobind Singh Indraprastha University, Dwarka Sector 16C, New Delhi 110078, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2207-2684","authenticated-orcid":true,"given":"Ravindra Kumar","family":"Purwar","sequence":"additional","affiliation":[{"name":"University School of Information and Communication Technology, Guru Gobind Singh Indraprastha University, Dwarka Sector 16C, New Delhi 110078, India"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2009.2013850"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.09.051"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2015.07.006"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2006.05.002"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2009.11.006"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2017.03.024"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2017.03.026"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-016-4171-y"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.2174\/1871527315666161024142036"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.2174\/1871527315666161026115046"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2017.06.038"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2006.12.001"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.11.034"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2011.02.012"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2016.09.021"},{"key":"19","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2017.01.018"},{"key":"23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.03.111"},{"key":"24","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2016.10.003"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2015.12.006"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2005.11.014"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2005.11.020"},{"key":"20","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2005.11.024"},{"key":"21","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2009.07.002"},{"key":"22","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2013.08.017"},{"key":"25","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2016.07.015"},{"key":"28","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2009.2038575"},{"year":"1999","key":"26"},{"key":"27","doi-asserted-by":"publisher","DOI":"10.1016\/j.talanta.2010.08.008"},{"issue":"3","key":"34","first-page":"598","volume":"4","year":"2015","journal-title":"International Journal of Emerging Technology and Advanced Engineering"},{"key":"33","doi-asserted-by":"publisher","DOI":"10.1111\/1467-9868.00196"},{"key":"31","doi-asserted-by":"publisher","DOI":"10.15326\/jcopdf.1.1.2014.0114"},{"key":"30"}],"container-title":["Applied Computational Intelligence and Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/acisc\/2017\/9571262.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/acisc\/2017\/9571262.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/acisc\/2017\/9571262.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,12,24]],"date-time":"2017-12-24T18:30:50Z","timestamp":1514140250000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/acisc\/2017\/9571262\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"references-count":32,"alternative-id":["9571262","9571262"],"URL":"https:\/\/doi.org\/10.1155\/2017\/9571262","relation":{},"ISSN":["1687-9724","1687-9732"],"issn-type":[{"type":"print","value":"1687-9724"},{"type":"electronic","value":"1687-9732"}],"subject":[],"published":{"date-parts":[[2017]]}}}