Classification of breast masses in mammogram images using KNN

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dc.authorscopusid55751834800
dc.authorscopusid56779609900
dc.authorscopusid56780481100
dc.authorscopusid15834365300
dc.contributor.authorAlpaslan N.
dc.contributor.authorKara A.
dc.contributor.authorZencir B.
dc.contributor.authorHanbay D.
dc.date.accessioned2024-08-04T20:04:01Z
dc.date.available2024-08-04T20:04:01Z
dc.date.issued2015
dc.departmentİnönü Üniversitesien_US
dc.description2015 23rd Signal Processing and Communications Applications Conference, SIU 2015 -- 16 May 2015 through 19 May 2015 -- 113052en_US
dc.description.abstractBreast cancer is one of the most deadly diseases for women. Mammogram is very important imaging technique used diagnosis in early stages of breast cancer. In this study, a decision support system which helps experts to examine mammogram images in the fight against breast cancer is developed. In this study, firstly several preprocesses are applied to mammogram to make image clear and segmentation of mass is provided with an appropriate threshold value. After the segmentation processes, features of the tumor mass are obtained. The obtained features are classified as normal, benign or malignant using kNN (k-nearest neighbours) classifiers. In this study, its have been were shown that, effect of kurtosis, skewness and wavelet energy features on classification performance is shown. As a result, it has been seen that, these features improve the classification performance. © 2015 IEEE.en_US
dc.identifier.doi10.1109/SIU.2015.7130121
dc.identifier.endpage1472en_US
dc.identifier.isbn9781467373869
dc.identifier.scopus2-s2.0-84939208229en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1469en_US
dc.identifier.urihttps://doi.org/10.1109/SIU.2015.7130121
dc.identifier.urihttps://hdl.handle.net/11616/92285
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2015 23rd Signal Processing and Communications Applications Conference, SIU 2015 - Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectClassification (of information)en_US
dc.subjectDecision support systemsen_US
dc.subjectDiseasesen_US
dc.subjectHigher order statisticsen_US
dc.subjectImage classificationen_US
dc.subjectImage segmentationen_US
dc.subjectMammographyen_US
dc.subjectNearest neighbor searchen_US
dc.subjectX ray screensen_US
dc.subjectBreast Canceren_US
dc.subjectBreast massen_US
dc.subjectClassification performanceen_US
dc.subjectK-nearest neighboursen_US
dc.subjectMammogram imagesen_US
dc.subjectSegmentation processen_US
dc.subjectThreshold-valueen_US
dc.subjectWavelet energy featureen_US
dc.subjectMedical imagingen_US
dc.titleClassification of breast masses in mammogram images using KNNen_US
dc.title.alternativeMamografi Imgelerindeki Kitlelerin KNN ile Siniflandirilmasien_US
dc.typeConference Objecten_US

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