Atlas Optimization for Deep Brain Stimulation

dc.accessRightsAnonymous*
dc.audienceScienceen_US
dc.contributor.authorVogel, Dorian
dc.contributor.authorWardell, Karin
dc.contributor.authorCoste, Jérôme
dc.contributor.authorLemaire, Jean-Jaques
dc.contributor.authorHemm-Ode, Simone
dc.contributor.editorJarm, Tomaz
dc.contributor.editorCvetkoska, Aleksandra
dc.contributor.editorMahnič-Kalamiza, Samo
dc.contributor.editorMiklavcic, Damijan
dc.date.accessioned2021-05-10T09:09:20Z
dc.date.available2021-05-10T09:09:20Z
dc.date.issued2020-11-30
dc.description.abstractAbstract : Electrical stimulation of the deep parts of the brain is the standard answer for patients subject to drug-refractory movement disorders. Collective analysis of data collected during surgeries are crucial in order to provide more systematic planning assistance and understanding the physiological mechanisms of action. To that end, the process of normalizing anatomies captured with Magnetic Resonance imaging across patients is a key component. In this work, we present the optimization of a workflow designed to create group-specific anatomical templates: a group template is refined iteratively using the results of successive non-linear image registrations with refinement steps in the in the basal-ganglia area. All non-linear registrations were executed using the Advanced Normalization Tools (ANTs) and the quality of the nor-malization was measured using spacial overlap of anatomical structures manually delineated during the planning of the surgery. The parameters of the workflow evaluated were: the use of multiple modalities sequentially or together during each registration to the template, the number of iterations in the template creation and the fine settings of the non-linear registration tool. Using the T1 and white matter attenuated inverse recovery modalities (WAIR) together produced the best results, especially in the center of the brain. The optimal numbers of iterations of the template creation were higher than those from the literature and our previous works. Finally, the setting of the non-linear registration tool that improved results the most was the activation of the registration with the native voxel sizes of images, as opposed to down-sampled version of the images. The normalization process was optimized over our previous study and allowed to obtain the best possible anatomical nor-malization of this specific group of patient. It will be used to summarize and analyze peri-operative measurements during test stimulation. The aim is that the conclusions obtained from this analysis will be useful for assistance during the planning of new surgeries.en_US
dc.description.urihttps://hal.archives-ouvertes.fr/hal-03009088en_US
dc.event.end2020-12-03
dc.event.start2020-11-29
dc.identifier.doi10.1007/978-3-030-64610-3_16
dc.identifier.urihttps://irf.fhnw.ch/handle/11654/32427
dc.language.isoenen_US
dc.publisherIFMBEen_US
dc.relation.ispartofEMBEC 2020: 8th European Medical and Biological Engineeringen_US
dc.spatialPortorožen_US
dc.subjectMovement disordersen_US
dc.subjectRegistrationen_US
dc.subjectOptimisationen_US
dc.subjectAtlasen_US
dc.titleAtlas Optimization for Deep Brain Stimulationen_US
dc.type04B - Beitrag Konferenzschrift*
dc.volume80en_US
dspace.entity.typePublication
fhnw.InventedHereYesen_US
fhnw.IsStudentsWorknoen_US
fhnw.PublishedSwitzerlandYesen_US
fhnw.ReviewTypeNo peer reviewen_US
fhnw.affiliation.hochschuleHochschule für Life Sciencesde_CH
fhnw.affiliation.institutInstitut für Medizintechnik und Medizininformatikde_CH
fhnw.pagination130-142en_US
fhnw.publicationStatePublisheden_US
relation.isAuthorOfPublication751f4aee-97bb-4592-91f2-6e3e4623de25
relation.isAuthorOfPublication.latestForDiscovery751f4aee-97bb-4592-91f2-6e3e4623de25
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