460-06-004 ISMRM Abstract

Automated Segmentation of Individual Cerebral Perfusion Territories from Vessel-Selective MRI by Deep Learning

Primary: Neuro - Blood Vessels

Secondary: Analysis Methods - Segmentation and Detection

460-06-004 · Imaging the Brain’s Microenvironment: From Glymphatics to Cognition · Tuesday, 12 May, 4:55 PM–5:50 PM · Digital Posters Row A

Keywords: Data Analysis Blood vessels Arterial spin labeling Deep Learning Segmentation Vessel-selective perfusion MRI

Accepted

Vincent Wohlfarth ¹, Nico Sollmann^1,2,3,4, Matthias Toth¹, Michael Helle⁵, Jan S Kirschke¹, Stephan Kaczmarz^1,2, Julia A Schnabel^6,7,8, Christine Preibisch^1,2,9, Hannah Eichhorn^6,7, Gabriel Hoffmann^1,2

¹Department of Diagnostic and Interventional Neuroradiology, TUM University Hospital, Munich, Germany

²TUM-Neuroimaging Center, TUM University Hospital, Munich, Germany

³Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany

⁴Department of Nuclear Medicine, University Hospital Ulm, Ulm, Germany

⁵Philips GmbH Innovative Technologies, Hamburg, Germany

⁶Institute of Machine Learning in Biomedical Imaging, Helmholtz Munich, Munich, Germany

⁷School of Computation, Information and Technology, Technical University Munich, Munich, Germany

⁸School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom

⁹Clinic of Neurology, TUM University Hospital, Munich, Germany

Presenting Author: Vincent Wohlfarth

Synopsis

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References

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Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/460-06-004