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Segmentation of the mouse skull for MRI guided transcranial focused ultrasound therapy planning

Hopp, Torsten ORCID iD icon 1; Springer, Luca 1; Gross, Carl 1; Grudzenski-Theis, Saskia; Mathis-Ullrich, Franziska 2; Ruiter, Nicole ORCID iD icon 1; Linte, Cristian A. [Hrsg.]; Siewerdsen, Jeffrey H. [Hrsg.]
1 Institut für Prozessdatenverarbeitung und Elektronik (IPE), Karlsruher Institut für Technologie (KIT)
2 Institut für Anthropomatik und Robotik (IAR), Karlsruher Institut für Technologie (KIT)


For opening the blood brain barrier using focused ultrasound (FUS) to treat neurodegenerative diseases, mouse- specific therapy planning is an essential step. For our therapy planning approach based on acoustic simulations we here propose to automatically segment the mouse skull and brain from magnetic resonance imaging, which is usually used in combination with FUS for monitoring purposes. The proposed method consists of (1) pre- processing to enhance the image contrast and remove noise, (2) a rough skull segmentation using morphological operations and adaptive binarization, (3) segmentation of the brain using the established 3D-PCNN method, (4) correction of the skull segmentation using the anatomical information about the brain location and (5) a post-processing to remove obvious errors from the final skull segmentation. The method is evaluated with four in-vivo datasets obtained with different parameters. The median Matthews Correlation Coefficient (MCC) on all slices of four datasets was 0.85 for the brain segmentation, 0.69 for the overall skull segmentation and 0.78 for the skull cap. Finally for showcasing the application an acoustic simulation based on the segmentation is presented, which results in a comparable prediction of the pressure field prediction as our earlier method based on micro-CT, and lines up well with literature estimations of the ultrasound attenuation.

Postprint §
DOI: 10.5445/IR/1000148095
Veröffentlicht am 05.04.2023
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Institut für Prozessdatenverarbeitung und Elektronik (IPE)
Publikationstyp Proceedingsbeitrag
Publikationsdatum 04.04.2022
Sprache Englisch
Identifikator ISBN: 978-1-5106-4944-6
ISSN: 1605-7422
KITopen-ID: 1000148095
HGF-Programm 54.12.03 (POF IV, LK 01) Science Systems
Erschienen in Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling. Ed.: C. A. Linte
Veranstaltung SPIE Medical Imaging (2022), San Diego, CA, USA, 20.02.2022 – 24.02.2022
Verlag SPIE
Seiten Art.-Nr.: 120341P
Serie Proceedings of SPIE ; 12034
Nachgewiesen in Scopus
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