{'fraction_non_alphanumeric': 0.01926444833625219, 'fraction_numerical': 0.0035026269702276708, 'mean_word_length': 5.0476190476190474, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Segmentation of infarct in acute ischemic stroke from MR apparent diffusion coefficient and trace-weighted images

Evidence from several previous studies indicated that apparent diffusion coefficient (ADC) map was likely to reveal brain regions belonging to the ischemic penumbra, that is, areas that may be at risk of infarction in a few hours following stroke onset. Trace map overcomes the anisotropic diffusions of ADC map, so it is superior for evaluation of an infarct involving white matter. Mean shift (MS) approach has been successfully used for image segmentation, particularly in brain MR images. The aim of the study was to develop a tool for rapid and reliable segmentation of infarct in human acute ischemic stroke based on the ADC and trace maps using the MS approach. In addition, a novel method of 3-dimensional visualization was presented to provide useful insights into volume datasets for clinical diagnosis. We applied the presented method to clinical data. The results showed that it was consistent, fast (about 8-10 minutes per subject) and indistinguishable from an expert using manual segmentation when used our tool.