Paper
21 May 2001 Tissue characterization in cerebral ischemia using multiparameter MRI
Hamid Soltanian-Zadeh, Rabih Hammoud, Michael A. Jacobs, Suresh C. Patel M.D., Panayiotis D. Mitsias M.D., Mamatha Pasnoor M.D., Robert Knight, Zhang G. Zheng M.D., Mei Lu, Michael Chopp
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Abstract
After pre-processing and segmentation, the proposed method scores tissue regions between 1 and N. Score 1 is assigned to normal white matter and score N to CSF. Lesion zones are assigned a score based on their relative levels of similarities to white matter and CSF. To evaluate the method, 15 rats were imaged by a 7T MRI system at one of the three time points (acute, sub-acute, chronic) after MCA occlusion. Then, they were sacrificed and their brains were sliced and prepared for histological studies. MRI of 2 or 3 slices of each rat brain, using 2 DWI (b equals 400, b equals 800), 1 PDWI, 1 T2WI, and 1 T1WI, was used and an MRI score between 1 and 100 (N equals 100) was found for each region. Segmented regions were mapped onto the histology images and were scored by an experienced pathologist, from 1 to 10. MRI scores were validated using histology scores. To this end, correlation coefficients between the two scores (MRI and histology) were found. The results showed excellent correlations between MRI and histology scores at different time points.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hamid Soltanian-Zadeh, Rabih Hammoud, Michael A. Jacobs, Suresh C. Patel M.D., Panayiotis D. Mitsias M.D., Mamatha Pasnoor M.D., Robert Knight, Zhang G. Zheng M.D., Mei Lu, and Michael Chopp "Tissue characterization in cerebral ischemia using multiparameter MRI", Proc. SPIE 4321, Medical Imaging 2001: Physiology and Function from Multidimensional Images, (21 May 2001); https://doi.org/10.1117/12.428162
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Cited by 1 scholarly publication.
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KEYWORDS
Magnetic resonance imaging

Tissues

Image segmentation

Brain

Image analysis

Ischemia

Diffusion weighted imaging

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