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dc.contributor.authorErtas, G
dc.contributor.authorDoran, SJ
dc.contributor.authorLeach, MO
dc.date.accessioned2016-11-23T10:54:18Z
dc.date.issued2017-01
dc.identifier.citationMedical & biological engineering & computing, 2017, 55 (1), pp. 57 - 68
dc.identifier.issn0140-0118
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/232
dc.identifier.eissn1741-0444
dc.identifier.doi10.1007/s11517-016-1484-y
dc.description.abstractDensity assessment and lesion localization in breast MRI require accurate segmentation of breast tissues. A fast, computerized algorithm for volumetric breast segmentation, suitable for multi-centre data, has been developed, employing 3D bias-corrected fuzzy c-means clustering and morphological operations. The full breast extent is determined on T1-weighted images without prior information concerning breast anatomy. Left and right breasts are identified separately using automatic detection of the midsternum. Statistical analysis of breast volumes from eighty-two women scanned in a UK multi-centre study of MRI screening shows that the segmentation algorithm performs well when compared with manually corrected segmentation, with high relative overlap (RO), high true-positive volume fraction (TPVF) and low false-positive volume fraction (FPVF), and has an overall performance of RO 0.94 ± 0.05, TPVF 0.97 ± 0.03 and FPVF 0.04 ± 0.06, respectively (training: 0.93 ± 0.05, 0.97 ± 0.03 and 0.04 ± 0.06; test: 0.94 ± 0.05, 0.98 ± 0.02 and 0.05 ± 0.07).
dc.formatPrint-Electronic
dc.format.extent57 - 68
dc.languageeng
dc.language.isoeng
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.subjectBreast
dc.subjectHumans
dc.subjectBreast Neoplasms
dc.subjectMagnetic Resonance Imaging
dc.subjectAlgorithms
dc.subjectImage Processing, Computer-Assisted
dc.subjectFemale
dc.titleA computerized volumetric segmentation method applicable to multi-centre MRI data to support computer-aided breast tissue analysis, density assessment and lesion localization.
dc.typeJournal Article
dcterms.dateAccepted2016-03-04
rioxxterms.versionofrecord10.1007/s11517-016-1484-y
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0
rioxxterms.licenseref.startdate2017-01
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfMedical & biological engineering & computing
pubs.issue1
pubs.notesNo embargo
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Magnetic Resonance
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Magnetic Resonance
pubs.publication-statusPublished
pubs.volume55
pubs.embargo.termsNo embargo
icr.researchteamMagnetic Resonanceen_US
dc.contributor.icrauthorDoran, Simonen
dc.contributor.icrauthorLeach, Martinen


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