Breast MR segmentation and lesion detection with cellular neural networks and 3D template matching

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dc.contributor.authorErtaş, Gökhan
dc.contributor.authorGülçür, H.Özcan
dc.contributor.authorOsman, Onur
dc.contributor.authorUçan, Osman N.
dc.contributor.authorTunacı, Mehtap
dc.contributor.authorDursun, Memduh
dc.date.accessioned2020-11-21T15:51:42Z
dc.date.available2020-11-21T15:51:42Z
dc.date.issued2008en_US
dc.departmentİstanbul Ticaret Üniversitesien_US
dc.descriptionPubMed ID: 17854795en_US
dc.description.abstractA novel fully automated system is introduced to facilitate lesion detection in dynamic contrast-enhanced, magnetic resonance mammography (DCE-MRM). The system extracts breast regions from pre-contrast images using a cellular neural network, generates normalized maximum intensity-time ratio (nMITR) maps and performs 3D template matching with three layers of 12 × 12 cells to detect lesions. A breast is considered to be properly segmented when relative overlap > 0.85 and misclassification rate < 0.10. Sensitivity, false-positive rate per slice and per lesion are used to assess detection performance. The system was tested with a dataset of 2064 breast MR images (344 slices × 6 acquisitions over time) from 19 women containing 39 marked lesions. Ninety-seven percent of the breasts were segmented properly and all the lesions were detected correctly (detection sensitivity = 100 %), however, there were some false-positive detections (31%/lesion, 10%/slice). © 2007 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.compbiomed.2007.08.001en_US
dc.identifier.endpage126en_US
dc.identifier.issn0010-4825
dc.identifier.issue1en_US
dc.identifier.pmid17854795en_US
dc.identifier.scopus2-s2.0-37049035589en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage116en_US
dc.identifier.urihttps://doi.org/10.1016/j.compbiomed.2007.08.001
dc.identifier.urihttps://hdl.handle.net/11467/3499
dc.identifier.volume38en_US
dc.identifier.wosWOS:000252918000013en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.relation.ispartofComputers in Biology and Medicineen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subject3D template matchingen_US
dc.subjectCellular neural networken_US
dc.subjectLesion detectionen_US
dc.subjectMR mammographyen_US
dc.subjectSegmentationen_US
dc.titleBreast MR segmentation and lesion detection with cellular neural networks and 3D template matchingen_US
dc.typeArticleen_US

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