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Evaluation of Ischemic Stroke Hybrid Segmentation in a Rat Model of Temporary Middle Cerebral Artery Occlusion using Ground Truth from Histologic and MR data

Imielinska, Celina Z.; Jin, Yinpeng; Liu, Xin; Rosiene, Joel; Zacharia, Brad E.; Komotar, Ricardo J.; Mocco, J.; Sughrue, Michael E.; Grobelny, Bartosz; Sisti, Alex; Silverberg, Josh; Khandji, Joyce; Cohen, Hillary; Connolly Jr., E. Sander; D'Ambrosio, Anthony Louis

A segmentation method that quantifies cerebral infarct using rat data with ischemic stroke is evaluated using ground truth from histologic and MR data. To demonstrate alternative approach to rapid quantification of cerebral infarct volumes using histologic stained slices that requires scarifying animal life, a study with MR acquire volumetric rat data is proposed where ground truth is obtained by manual delineations by experts and automated segmentation is assessed for accuracy. A framework for evaluation of segmentation is used that provides more detailed accuracy measurements than mere cerebral infarct volume. Our preliminary experiment shows that ground truth derived from MRI data is at least as good as the one obtained from the histologic slices for evaluating segmentation algorithms for accuracy. Therefore we can develop and evaluate automated segmentation methods for rapid quantification of stroke without the necessitating animal sacrifice.

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Also Published In

Title
Medical Imaging 2005: Image Processing
Publisher
SPIE
DOI
https://doi.org/10.1117/12.596662

More About This Work

Academic Units
Biomedical Informatics
Computer Science
Biomedical Engineering
Neurological Surgery
Series
Proceedings of SPIE, 5747
Published Here
September 29, 2014
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