Automatic detection and quantification of acute cerebral infarct by fuzzy clustering and histographic characterization on diffusion weighted MR imaging and apparent diffusion coefficient map.

ABSTRACT: Determination of the volumes of acute cerebral infarct in the magnetic resonance imaging harbors prognostic values. However, semiautomatic method of segmentation is time-consuming and with high interrater variability. Using diffusion weighted imaging and apparent diffusion coefficient map from patients with acute infarction in 10 days, we aimed to develop a fully automatic algorithm to measure infarct volume. It includes an unsupervised classification with fuzzy C-means clustering determination of the histographic distribution, defining self-adjusted intensity thresholds. The proposed method attained high agreement with the semiautomatic method, with similarity index 89.9 ± 6.5%, in detecting cerebral infarct lesions from 22 acute stroke patients. We demonstrated the accuracy of the propos

SUBMITTER: Tsai JZ 

PROVIDER: S-EPMC3971548 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature