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Patch-based field-of-view matching in multi-modal images for electroporation-based ablations

hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorLAFITTE, Luc
hal.structure.identifierLaboratoire de l'intégration, du matériau au système [IMS]
dc.contributor.authorGIRAUD, Rémi
hal.structure.identifierUniversity Medical Center [Utrecht] [UMCU]
dc.contributor.authorZACHIU, Cornel
hal.structure.identifierUniversity Medical Center [Utrecht] [UMCU]
dc.contributor.authorRIES, Mario
hal.structure.identifierHôpital Jean Verdier [AP-HP]
dc.contributor.authorSUTTER, Olivier
hal.structure.identifierHôpital Jean Verdier [AP-HP]
dc.contributor.authorPETIT, Antoine
hal.structure.identifierHôpital Jean Verdier [AP-HP]
dc.contributor.authorSEROR, Olivier
hal.structure.identifierModélisation Mathématique pour l'Oncologie [MONC]
dc.contributor.authorPOIGNARD, Clair
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierModélisation Mathématique pour l'Oncologie [MONC]
dc.contributor.authorDENIS DE SENNEVILLE, Baudouin
dc.date.accessioned2024-04-04T02:52:14Z
dc.date.available2024-04-04T02:52:14Z
dc.date.issued2020
dc.identifier.issn0895-6111
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/192047
dc.description.abstractEnVarious multi-modal imaging sensors are currently involved at different steps of an interventional therapeutic work-flow. Cone beam computed tomography (CBCT), computed tomography (CT) or Magnetic Resonance (MR) images thereby provides complementary functional and/or structural information of the targeted region and organs at risk. Merging this information relies on a correct spatial alignment of the observed anatomy between the acquired images. This can be achieved by the means of multi-modal deformable image registration (DIR), demonstrated to be capable of estimating dense and elastic deformations between images acquired by multiple imaging devices. However, due to the typically different field-of-view (FOV) sampled across the various imaging modalities, such algorithms may severely fail in finding a satisfactory solution. In the current study we propose a new fast method to align the FOV in multi-modal 3D medical images. To this end, a patch-based approach is introduced and combined with a state-of-the-art multi-modal image similarity metric in order to cope with multi-modal medical images. The occurrence of estimated patch shifts is computed for each spatial direction and the shift value with maximum occurrence is selected and used to adjust the image field-of-view. The performance of the proposed method-in terms of both registration accuracy and computational needs-is analyzed in the practical case of on-line irreversible electroporation procedures. In total, 30 pairs of pre-/per-operative IRE images are considered to illustrate the efficiency of our algorithm. We show that a regional registration approach using voxel patches provides a good structural compromise between the voxel-wise and "global shifts" approaches. The method was thereby beneficial for CT to CBCT and MRI to CBCT registration tasks, especially when highly different image FOVs are involved. Besides, the benefit of the method for CT to CBCT and MRI to CBCT image registration is analyzed, including the impact of artifacts generated by percutaneous needle insertions. Additionally, the computational needs using commodity hardware are demonstrated to be compatible with clinical constraints in the practical case of on-line procedures. The proposed patch-based workflow thus represents an attractive asset for DIR at different stages of an interventional procedure.
dc.description.sponsorshipInitiative d'excellence de l'Université de Bordeaux - ANR-10-IDEX-0003
dc.language.isoen
dc.publisherElsevier
dc.subject.enPatch-based matching
dc.subject.enMulti-modal image registration
dc.subject.enInterventional procedures
dc.title.enPatch-based field-of-view matching in multi-modal images for electroporation-based ablations
dc.typeArticle de revue
dc.identifier.doi10.1016/j.compmedimag.2020.101750
dc.subject.halSciences de l'ingénieur [physics]/Traitement du signal et de l'image
dc.subject.halMathématiques [math]/Equations aux dérivées partielles [math.AP]
bordeaux.journalComputerized Medical Imaging and Graphics
bordeaux.volume84
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-02868718
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02868718v1
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