Abstract
The accurate segmentation of lesions in magnetic resonance images of stroke patients is important, for example, for comparing the location of the lesion with functional areas and for determining the optimal strategy for patient treatment. Manual labeling of each lesion turns out to be time-intensive and costly, making an automated method desirable. Standard approaches for brain parcellation make use of spatial atlases that represent prior information about the spatial distribution of different tissue types and of anatomical structures of interest. Different from healthy tissue, however, the spatial distribution of a stroke lesion varies considerably, limiting the use of such brain image segmentation approaches for stroke lesion analysis, and for integrating brain parcellation with stroke lesion segmentation. We propose to amend the standard atlas-based generative image segmentation model by a spatial atlas of stroke lesion occurrence by making use of information about the vascular territories. As the territories of the major arterial trees often coincide with the location and extensions of large stroke lesions, we use 3D maps of the vascular territories to form patient-specific atlases combined with outlier information from an initial run, following an iterative procedure. We find our approach to perform comparable to (or better than) standard approaches that amend the tissue atlas with a flat lesion prior or that treat lesion as outliers, and to outperform both for large heterogeneous lesions.
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Derntl, A., Plant, C., Gruber, P., Wegener, S., Bauer, J.S., Menze, B.H. (2016). Stroke Lesion Segmentation Using a Probabilistic Atlas of Cerebral Vascular Territories. In: Crimi, A., Menze, B., Maier, O., Reyes, M., Handels, H. (eds) Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2015. Lecture Notes in Computer Science(), vol 9556. Springer, Cham. https://doi.org/10.1007/978-3-319-30858-6_3
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DOI: https://doi.org/10.1007/978-3-319-30858-6_3
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