Abstract #4769
Automatic Two Stage Classification and Segmentation of Ischemic Stroke Lesions in Diffusion-Weighted MRI
Pieter C. Vos 1,2 , Steven Mocking 2 , Priya Garg 2 , Aurauma Chutinet 3 , William A. Copen 4 , Max A. Viergever 1 , and Ona Wu 2
1
Radiology, Image Sciences Institute,
Utrecht, Utrecht, Netherlands,
2
Athinoula
A. Martinos Center for Biomedical Imaging, Massachusetts
General Hospital, Boston, Massachusetts, United States,
3
Department
of Neurorology, MGH, Massachusetts, United States,
4
Department
of Radiology, MGH, Massachusetts, United States
DWI is a reliable and routinely-used modality in the
acute setting of ischemic stroke. Automated approaches
for outlining the DWI lesion have the potential to
assist in the rapid assessment of lesion volumetry in
the acute setting of stroke. Our results demonstrate
that the segmentation performance of pixel
classification approach can be significantly improved
with regional analysis, i.e. using a supervised
classifier that discriminates false detected regions
from true lesion regions in a two-stage classification
approach.
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