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Abstract #0895

Feasibility study on automated white matter tract segmentation in neurosurgical pre-operative planning

Daniel Güllmar1, Rotraud Neumann2, Jakob Wasserthal3, Jan Walter4, Ulf KM Teichgräber5, Thomas E Mayer2, and Jürgen R Reichenbach1,6

1Medical Physics Group, Inst. of Diagnostic and Interventional Radiology, Jena University Hospital, Jena, Germany, 2Section of Neuroradiology, Inst. of Diagnostic and Interv. Radiology, Jena University Hospital, Jena, Germany, 3Division of Medical Image Computing (MIC), German Cancer Research Center (DKFZ), Heidelberg, Germany, 4Department of Neurosurgery, Jena University Hospital, Jena, Germany, 5Inst. of Diagnostic and Interventional Radiology, Jena University Hospital, Jena, Germany, 6Michel-Stifel-Center-Jena for Data-Driven and Simulation Science, Friedrich-Schiller-University Jena, Jena, Germany

In neuro-surgical preoperative planning of extirpation of large tumors it is important to locate the paths of critical cerebral nerve fiber bundles (e.g. corticospinal-tract). Manual fiber bundle selection is elaborate, requires expert knowledge and is prone to user errors. Therefore, in this study a fully automatic pipeline for white matter bundle segmentation was setup, incorporating recently published white matter bundle segmentation based using DNN, and tested with 12 patients suffering from large brain lesions. In all cases the position of the corticospinal tracts was evaluated as plausible, although in at least one hemisphere this tract was affected by the lesion.

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