Multivariate Analysis of Ischaemic Lesions Using Computed Tomography and CT Perfusion Imaging: Critical Review

Abstract

ABSTRACT Stroke is characterised as a cerebrovascular disease, which acts as the key factor of mortality and permanent disabilities. Ischaemic stroke is observed as a widespread stroke that results in tissue hypoxia. Hence, it is crucial to analyse the ischaemic stroke lesions for the accurate identification of the stroke in intensive care units. However, the recognition of ischaemic lesions is a difficult process due to their small resolution and poor image resolution. Various schemes have been suggested for stroke lesion identification, localisation, and detection, finding infarct cores and penumbras is of high interest. Artificial intelligence could be one of the promising technologies in all methods, which may accelerate stroke analysis and lead to improved patient recovery. This article provides a review of different articles related to ischaemic lesion deduction using Computed Tomography (CT) and CT perfusion imaging. This review article thus provides insight into methods, performance measures, and the key highlight of these models. Further, this review article provides the challenges encountered in the existing techniques.