Computerized Method for Nonrigid Mr-To Breast-Image Registration

dc.contributor.author Ünlü, Mehmet Zübeyir
dc.contributor.author Krol, A.
dc.contributor.author Magri, A.
dc.contributor.author Mandel, J. A.
dc.contributor.author Lee, W.
dc.contributor.author Baum, K. G.
dc.contributor.author Lipson, E. D.
dc.contributor.author Coman, I. L.
dc.contributor.author Feiglin, D. H.
dc.coverage.doi 10.1016/j.compbiomed.2009.10.010
dc.date.accessioned 2017-01-17T07:39:55Z
dc.date.available 2017-01-17T07:39:55Z
dc.date.issued 2010
dc.description.abstract We have developed and tested a new simple computerized finite element method (FEM) approach to MR-to-PET nonrigid breast-image registration. The method requires five-nine fiducial skin markers (FSMs) visible in MRI and PET that need to be located in the same spots on the breast and two on the flanks during both scans. Patients need to be similarly positioned prone during MRI and PET scans. This is accomplished by means of a low gamma-ray attenuation breast coil replica used as the breast support during the PET scan. We demonstrate that, under such conditions, the observed FSM displacement vectors between MR and PET images, distributed piecewise linearly over the breast volume, produce a deformed FEM mesh that reasonably approximates nonrigid deformation of the breast tissue between the MRI and PET scans. This method, which does not require a biomechanical breast tissue model, is robust and fast. Contrary to other approaches utilizing voxel intensity-based similarity measures or surface matching, our method works for matching MR with pure molecular images (i.e. PET or SPECT only). Our method does not require a good initialization and would not be trapped by local minima during registration process. All processing including FSMs detection and matching, and mesh generation can be fully automated. We tested our method on MR and PET breast images acquired for 15 subjects. The procedure yielded good quality images with an average target registration error below 4 mm (i.e. well below PET spatial resolution of 6-7 mm). Based on the results obtained for 15 subjects studied to date, we conclude that this is a very fast and a well-performing method for MR-to-PET breast-image nonrigid registration. Therefore, it is a promising approach in clinical practice. This method can be easily applied to nonrigid registration of MRI or CT of any type of soft-tissue images to their molecular counterparts such as obtained using PET and SPECT. © 2009 Elsevier Ltd. All rights reserved. en_US
dc.identifier.citation Ünlü, M. Z., Krol, A., Magri, A., Mandel, J. A., Lee, W., Baum, K. G., Lipson, E. D., Coman, I. L., and Feiglin, D. H. (2010). Computerized method for nonrigid MR-to-PET breast-image registration. Computers in Biology and Medicine, 40(1), 37-53. doi:10.1016/j.compbiomed.2009.10.010 en_US
dc.identifier.doi 10.1016/j.compbiomed.2009.10.010 en_US
dc.identifier.doi 10.1016/j.compbiomed.2009.10.010
dc.identifier.issn 0010-4825
dc.identifier.scopus 2-s2.0-74149086948
dc.identifier.uri http://doi.org/10.1016/j.compbiomed.2009.10.010
dc.identifier.uri https://hdl.handle.net/11147/2801
dc.language.iso en en_US
dc.publisher Elsevier Ltd. en_US
dc.relation.ispartof Computers in Biology and Medicine en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Image registration en_US
dc.subject Biomechanics en_US
dc.subject Electromagnetic wave attenuation en_US
dc.subject Gamma rays en_US
dc.subject Positron emission tomography en_US
dc.title Computerized Method for Nonrigid Mr-To Breast-Image Registration en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.institutional Ünlü, Mehmet Zübeyir
gdc.author.yokid 42462
gdc.bip.impulseclass C5
gdc.bip.influenceclass C4
gdc.bip.popularityclass C4
gdc.coar.access open access
gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.department İzmir Institute of Technology. Electrical and Electronics Engineering en_US
gdc.description.endpage 53 en_US
gdc.description.issue 1 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q1
gdc.description.startpage 37 en_US
gdc.description.volume 40 en_US
gdc.description.wosquality Q1
gdc.identifier.openalex W2053848283
gdc.identifier.pmid 19942214
gdc.identifier.wos WOS:000274948300005
gdc.index.type WoS
gdc.index.type Scopus
gdc.index.type PubMed
gdc.oaire.accesstype BRONZE
gdc.oaire.diamondjournal false
gdc.oaire.impulse 4.0
gdc.oaire.influence 3.767933E-9
gdc.oaire.isgreen true
gdc.oaire.keywords Positron emission tomography
gdc.oaire.keywords Gamma rays
gdc.oaire.keywords Finite Element Analysis
gdc.oaire.keywords Middle Aged
gdc.oaire.keywords Magnetic Resonance Imaging
gdc.oaire.keywords Imaging, Three-Dimensional
gdc.oaire.keywords Positron-Emission Tomography
gdc.oaire.keywords Image Processing, Computer-Assisted
gdc.oaire.keywords Humans
gdc.oaire.keywords Biomechanics
gdc.oaire.keywords Female
gdc.oaire.keywords Breast
gdc.oaire.keywords Electromagnetic wave attenuation
gdc.oaire.keywords Image registration
gdc.oaire.keywords Algorithms
gdc.oaire.popularity 5.944805E-9
gdc.oaire.publicfunded false
gdc.oaire.sciencefields 03 medical and health sciences
gdc.oaire.sciencefields 0302 clinical medicine
gdc.openalex.collaboration International
gdc.openalex.fwci 0.52485221
gdc.openalex.normalizedpercentile 0.7
gdc.opencitations.count 23
gdc.plumx.crossrefcites 12
gdc.plumx.mendeley 46
gdc.plumx.pubmedcites 1
gdc.plumx.scopuscites 26
gdc.scopus.citedcount 26
gdc.wos.citedcount 21
relation.isAuthorOfPublication.latestForDiscovery 096da1f6-0d36-4fe5-a83c-3a7ff0665b4b
relation.isOrgUnitOfPublication.latestForDiscovery 9af2b05f-28ac-4018-8abe-a4dfe192da5e

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