{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T16:55:41Z","timestamp":1790787341668,"version":"4.1.0"},"reference-count":80,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2018,8,3]],"date-time":"2018-08-03T00:00:00Z","timestamp":1533254400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2018,9]]},"abstract":"<jats:sec><jats:title>Purpose<\/jats:title><jats:p>This work proposes a new reliable computer\u2010aided diagnostic (<jats:styled-content style=\"fixed-case\">CAD<\/jats:styled-content>) system for the diagnosis of breast cancer from breast ultrasound (<jats:styled-content style=\"fixed-case\">BUS<\/jats:styled-content>) images. The system can be useful to reduce the number of biopsies and pathological tests, which are invasive, costly, and often unnecessary.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>The proposed <jats:styled-content style=\"fixed-case\">CAD<\/jats:styled-content> system classifies breast tumors into benign and malignant classes using morphological and textural features extracted from breast ultrasound (<jats:styled-content style=\"fixed-case\">BUS<\/jats:styled-content>) images. The images are first preprocessed to enhance the edges and filter the speckles. The tumor is then segmented semiautomatically using the watershed method. Having the tumor contour, a set of 855 features including 21 shape\u2010based, 810 contour\u2010based, and 24 textural features are extracted from each tumor. Then, a Bayesian Automatic Relevance Detection (<jats:styled-content style=\"fixed-case\">ARD<\/jats:styled-content>) mechanism is used for computing the discrimination power of different features and dimensionality reduction. Finally, a logistic regression classifier computed the posterior probabilities of malignant vs benign tumors using the reduced set of features.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>A dataset of 104 <jats:styled-content style=\"fixed-case\">BUS<\/jats:styled-content> images of breast tumors, including 72 benign and 32 malignant tumors, was used for evaluation using an eightfold cross\u2010validation. The algorithm outperformed six state\u2010of\u2010the\u2010art methods for <jats:styled-content style=\"fixed-case\">BUS<\/jats:styled-content> image classification with large margins by achieving 97.12% accuracy, 93.75% sensitivity, and 98.61% specificity rates.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Using <jats:styled-content style=\"fixed-case\">ARD<\/jats:styled-content>, the proposed <jats:styled-content style=\"fixed-case\">CAD<\/jats:styled-content> system selects five new features for breast tumor classification and outperforms state\u2010of\u2010the\u2010art, making a reliable and complementary tool to help clinicians diagnose breast cancer.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mp.13082","type":"journal-article","created":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T12:06:39Z","timestamp":1530792399000},"page":"4112-4124","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Classification of breast lesions in ultrasonography using sparse logistic regression and morphology\u2010based texture features"],"prefix":"10.1002","volume":"45","author":[{"given":"Hoda","family":"Nemat","sequence":"first","affiliation":[{"name":"Department of Electronic and Electrical Engineering Center for Computational Imaging Simulation Technologies in Biomedicine (CISTIB) University of Sheffield Sheffield S1 3JD UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hamid","family":"Fehri","sequence":"additional","affiliation":[{"name":"Department of Electronic and Electrical Engineering Center for Computational Imaging Simulation Technologies in Biomedicine (CISTIB) University of Sheffield Sheffield S1 3JD UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nasrin","family":"Ahmadinejad","sequence":"additional","affiliation":[{"name":"Department of Radiology Faculty of Medicine Tehran University of Medical Sciences Tehran 1416753955 Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alejandro F.","family":"Frangi","sequence":"additional","affiliation":[{"name":"Department of Electronic and Electrical Engineering Center for Computational Imaging Simulation Technologies in Biomedicine (CISTIB) University of Sheffield Sheffield S1 3JD UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Gooya","sequence":"additional","affiliation":[{"name":"Department of Electronic and Electrical Engineering Center for Computational Imaging Simulation Technologies in Biomedicine (CISTIB) University of Sheffield Sheffield S1 3JD UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2018,8,3]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1166\/jmihi.2014.1269"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2009.05.012"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.clinimag.2012.09.024"},{"key":"e_1_2_8_5_1","first-page":"293","article-title":"Analysis of contourlet texture feature extraction to classify the benign and malignant tumors from breast ultrasound images","volume":"6","author":"Telagarapu P","year":"2014","journal-title":"Int J Eng Technol"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2009.06.002"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.2174\/1874431101105010026"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.5405\/jmbe.30.5.06"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1259\/dmfr\/18407834"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.3265959"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultrasmedbio.2014.06.005"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2014.06.006"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10549-004-2043-z"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2014.07.026"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.medengphy.2009.10.007"},{"key":"e_1_2_8_16_1","unstructured":"G\u00f3mezW PereiraWCA InfantosiAFC D\u00edaz\u2010P\u00e9rezA.Computerized diagnosis of breast lesions on ultrasonography.XXII Brazilian Congr Biomed Eng;2010:399\u2013402."},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2262011843"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.7863\/jum.2004.23.9.1201"},{"key":"e_1_2_8_19_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/978-3-319-28495-8_1","article-title":"Artificial neural network modelling","volume":"628","author":"Shanmuganathan S","year":"2016","journal-title":"Stud Comput Intell"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2012.07.004"},{"key":"e_1_2_8_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2007.04.016"},{"key":"e_1_2_8_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0004-3702(97)00043-X"},{"key":"e_1_2_8_23_1","first-page":"71","article-title":"Computer aided system for breast cancer diagnosis in ultrasound images","volume":"76","author":"Abdelwahed NMA","year":"2015","journal-title":"J Ecol Heal Environ"},{"key":"e_1_2_8_24_1","first-page":"238","article-title":"Segmentation and classification of breast lesions in ultrasound images","volume":"3","author":"Lokesh B","year":"2014","journal-title":"Int J Sci Technology Res"},{"key":"e_1_2_8_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-013-9593-8"},{"key":"e_1_2_8_26_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.4766268"},{"key":"e_1_2_8_27_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-010-9624-7"},{"key":"e_1_2_8_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10396-010-0278-3"},{"key":"e_1_2_8_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2008.01.010"},{"key":"e_1_2_8_30_1","doi-asserted-by":"crossref","unstructured":"HorschK CeballosAF GigerML et\u00a0al.Optimizing feature selection across a multimodality database in computerized classification of breast lesions. In:Medical Imaging 2002. International Society for Optics and Photonics;2002:986\u2013992.","DOI":"10.1117\/12.467053"},{"key":"e_1_2_8_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-002-5038-5"},{"key":"e_1_2_8_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2004.12.016"},{"key":"e_1_2_8_33_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-005-0019-5"},{"key":"e_1_2_8_34_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultrasmedbio.2015.03.003"},{"key":"e_1_2_8_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2013.2279938"},{"key":"e_1_2_8_36_1","first-page":"72591S","article-title":"A comparative study in ultrasound breast imaging classification","volume":"7259","author":"Yap MH","year":"2009","journal-title":"SPIE Med Imaging Int Soc Opt Photonics"},{"key":"e_1_2_8_37_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2015.10.015"},{"key":"e_1_2_8_38_1","doi-asserted-by":"publisher","DOI":"10.1155\/2017\/3640901"},{"key":"e_1_2_8_39_1","first-page":"447","article-title":"Deep belief network for the enhancement of ultrasound images with pelvic lesions","author":"Shelgaonkar SL","year":"2017","journal-title":"J Intell Syst"},{"key":"e_1_2_8_40_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1992.4.3.415"},{"key":"e_1_2_8_41_1","volume-title":"Research and Development in Breast Ultrasound","author":"Ueno E","year":"2006"},{"key":"e_1_2_8_42_1","doi-asserted-by":"crossref","unstructured":"ZuiderveldK.Contrast limited adaptive histogram equalization chapter VIII.5. In:HeckbertPS ed.Graphics Gems IV.Cambridge MA:Academic Press;1994:474\u2013485.","DOI":"10.1016\/B978-0-12-336156-1.50061-6"},{"key":"e_1_2_8_43_1","volume-title":"Algorithms for Graphics and Image Processing","author":"Pavlidis T","year":"2012"},{"key":"e_1_2_8_44_1","unstructured":"SoftwareG.Didger 5 Full User's Guide \u2013 Golden Software;2013."},{"key":"e_1_2_8_45_1","unstructured":"FischerU BaumF Luftner\u2010NagelS.Direct Diagnosis in Radiology: Breast Imaging.New York:Thieme;2008."},{"key":"e_1_2_8_46_1","doi-asserted-by":"crossref","unstructured":"KasaudhanR HeoTK JeonSI SonSH.Similarity measurement with combination of mesh distance fourier transform and global features in 2D binary image. In:Proceedings of the 2015 Conference on Research in Adaptive and Convergent Systems;2016:2176\u20132181.","DOI":"10.1145\/2811411.2811506"},{"key":"e_1_2_8_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/34.368168"},{"key":"e_1_2_8_48_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compositesa.2014.03.020"},{"key":"e_1_2_8_49_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2014.11.007"},{"key":"e_1_2_8_50_1","unstructured":"VargaD.American Hand Sign Recognition in Video Streams.VII. Magyar Sz\u00e1m\u00edt\u00f3g\u00e9pes Grafika \u00c9s Geometria Konferencia;2014:162\u2013166."},{"key":"e_1_2_8_51_1","unstructured":"YangM KpalmaK RonsinJ.A survey of shape feature extraction techniques. In:Pattern Recognition;2008:43\u201390."},{"key":"e_1_2_8_52_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2004.09.001"},{"key":"e_1_2_8_53_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.image.2009.04.001"},{"key":"e_1_2_8_54_1","doi-asserted-by":"publisher","DOI":"10.5815\/ijigsp.2015.01.05"},{"key":"e_1_2_8_55_1","first-page":"1","article-title":"Computer\u2010aided diagnosis of breast tumor based on B\u2010mode ultrasound and color Doppler flow imaging","author":"Diao X\u2010F","year":"2009","journal-title":"2nd International Conference on Biomedical Engineering and Informatics, 2009"},{"key":"e_1_2_8_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2004.834617"},{"key":"e_1_2_8_57_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-010-9461-8"},{"key":"e_1_2_8_58_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0031-2023(97)00122-2"},{"key":"e_1_2_8_59_1","doi-asserted-by":"publisher","DOI":"10.1109\/TC.1972.5008949"},{"key":"e_1_2_8_60_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2005.860606"},{"key":"e_1_2_8_61_1","first-page":"2338","volume":"4","author":"Silva PD","year":"2015","journal-title":"Various shape descriptors in image processing \u2013 a review"},{"key":"e_1_2_8_62_1","unstructured":"Gonz\u00e1lezRC WoodsRE.Digital Image Processing Using MATLAB Vol.624.Upper Saddle River New Jersey:Pearson\u2010Prentice\u2010Hall 2004."},{"key":"e_1_2_8_63_1","doi-asserted-by":"publisher","DOI":"10.1117\/1.2713758"},{"key":"e_1_2_8_64_1","doi-asserted-by":"publisher","DOI":"10.1109\/42.650876"},{"key":"e_1_2_8_65_1","doi-asserted-by":"publisher","DOI":"10.1117\/12.191329"},{"key":"e_1_2_8_66_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jfranklin.2006.09.003"},{"key":"e_1_2_8_67_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10911-006-9018-0"},{"key":"e_1_2_8_68_1","doi-asserted-by":"crossref","unstructured":"SahinerB ChanH\u2010P PetrickN GoodsittMM HelvieMA.Characterization of masses on mammograms: Significance of using the rubber\u2010band straightening transform. In:Proceedings of SPIE \u2013 The International Society for Optical Engineering. Vol.3034;1997:491\u2013500.","DOI":"10.1117\/12.274135"},{"key":"e_1_2_8_69_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.598228"},{"key":"e_1_2_8_70_1","doi-asserted-by":"publisher","DOI":"10.1117\/12.237963"},{"key":"e_1_2_8_71_1","doi-asserted-by":"crossref","unstructured":"BuciuI GacsadiA.Gabor wavelet based features for medical image analysis and classification.2009 2nd Int Symp Appl Sci Biomed Commun Technol;2009:1\u20134.","DOI":"10.1109\/ISABEL.2009.5373659"},{"key":"e_1_2_8_72_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2010.10.003"},{"key":"e_1_2_8_73_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2014.05.008"},{"key":"e_1_2_8_74_1","doi-asserted-by":"publisher","DOI":"10.1109\/42.952732"},{"key":"e_1_2_8_75_1","first-page":"573","article-title":"Classification of mammographic images using Gabor wavelet and discrete wavelet transform","volume":"2","author":"Salve MSM","year":"2013","journal-title":"Int J Adv Res Electron Commun Eng"},{"key":"e_1_2_8_76_1","doi-asserted-by":"crossref","unstructured":"MirzapourF GhassemianH.Using GLCM and Gabor Filters for Classification of PAN Images. In:Electrical Engineering (ICEE) 2013 21st Iranian Conference on IEEE;2013.","DOI":"10.1109\/IranianCEE.2013.6599565"},{"key":"e_1_2_8_77_1","first-page":"529","article-title":"Intensity\u2010Invariant Texture Features for Breast Ultrasound Classification","volume":"1","author":"G\u00f3mez W","year":"2014","journal-title":"XXIV Congresso Brasileiro de Engenharia Biom\u00e9dica \u2014 CBEB"},{"key":"e_1_2_8_78_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2008.05.050"},{"key":"e_1_2_8_79_1","unstructured":"SocialiumR Oeconomicarumque.Theory and Implementation of Anticipatory Data Mining;2006."},{"key":"e_1_2_8_80_1","doi-asserted-by":"crossref","unstructured":"Rodr\u00edguez\u2010CristernaA G\u00f3mez\u2010FloresW de Albuquerque PereiraWC.BUSAT\u202f: A MATLAB Toolbox for Breast Ultrasound Image Analysis;2017;1:268\u2013277.","DOI":"10.1007\/978-3-319-59226-8_26"},{"key":"e_1_2_8_81_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-45528-0"}],"container-title":["Medical Physics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fmp.13082","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mp.13082","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,18]],"date-time":"2023-09-18T09:25:32Z","timestamp":1695029132000},"score":1,"resource":{"primary":{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/10.1002\/mp.13082"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,3]]},"references-count":80,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2018,9]]}},"alternative-id":["10.1002\/mp.13082"],"URL":"https:\/\/doi.org\/10.1002\/mp.13082","archive":["Portico"],"relation":{},"ISSN":["0094-2405","2473-4209"],"issn-type":[{"value":"0094-2405","type":"print"},{"value":"2473-4209","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,8,3]]},"assertion":[{"value":"2017-07-17","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2018-04-29","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2018-08-03","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}