Abstract
Noncontrast Computed Tomography (NCCT) of the brain has been the first-line diagnosis for emergency evaluation of acute stroke, so a rapid and automated detection, localization, and/or segmentation of ischemic lesions is of great importance. We provide the state-of-the-art review of methods for automated detection, localization, and/or segmentation of ischemic lesions on NCCT in human brain scans along with their comparison, evaluation, and classification. Twenty-two methods are (1) reviewed and evaluated; (2) grouped into image processing and analysis-based methods (11 methods), brain atlas-based methods (two methods), intensity template-based methods (1 method), Stroke Imaging Marker-based methods (two methods), and Artificial Intelligence-based methods (six methods); and (3) properties of these groups of methods are characterized. A new method classification scheme is proposed as a 2 × 2 matrix with local versus global processing and analysis, and density versus spatial sampling. Future studies are necessary to develop more efficient methods directed toward deep learning methods as well as combining the global methods with a high sampling both in space and density for the merged radiologic and neurologic data.
Highlights
Stroke is a major reason for permanent disability and a leading cause of death, which affects public health and results in large costs (Katan & Luft, 2018)
A number of various methods have been proposed for automated detection, localization, and/or segmentation of ischemic lesions on Noncontrast Computed Tomography (NCCT) in human brain scans
(several weeks after the stroke onset) to chronic infarcts. This difference in data selection for the same method was demonstrated, for instance, by Sales Barros et al (2019), where the performance measured by the Dice’s Similarity Coefficient (DSC) ranged from 37% for the subtle infarct class to 78% for the severe infarct class; as well as by Nowinski et al (2013) for the detection accuracy raising from of 78.4% for cases with ≥3 h from the stroke onset to 87.9% for cases with 8
Summary
Stroke is a major reason for permanent disability and a leading cause of death, which affects public health and results in large costs (Katan & Luft, 2018). Noncontrast Computed Tomography (NCCT) remains the first-line diagnosis for emergency evaluation of acute stroke because it is fast, widely available, cost-efficient, and reliably rules out hemorrhage (Lövblad & Baird, 2010). Ischemic changes in NCCT scans are characterized by several features including the presence of hypodensity. Localization, and segmentation in noncontrast CT human brain scans: review of automated methods. We have observed the presence of the hyperdense posterior cerebral artery sign (Ambrosius et al, 2011). NCCT, has poor sensitivity, in the first few hours, as acute ischemic changes on NCCT are subtle and often do not show infarct until 12–24 h after stroke onset (James et al, 2006). When compared to MR, this sensitivity is 25% in NCCT versus 86% in MR; within the first 3 h, it is lowered to 7% for NCCT and 46% for MR (Chalela et al, 2007)
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