The fractal analysis technique has emerged as a novel and promising method in mathematical analysis, providing valuable insights across various fields of neuroimaging. The fractal analysis technique allows for the quantitative characterization of complex geometric structures that traditional Euclidean geometry-based morphometric methods fail to describe adequately. This review provides an overview of the principles, characteristics, and main applications of the fractal analysis technique, focusing on its applications and perspectives in stroke diagnosis based on neuroimaging data. In stroke research, the fractal analysis technique has been used to characterize brain tissue, pathological foci, and the vascular network, providing critical diagnostic and prognostic information. Researchers have applied the fractal analysis technique to brain lesions resulting from ischemic strokes to conduct geometric analyses of lesion shapes, indicating its diagnostic and prognostic values. Fractal properties have been used to study the texture of lesions, healthy tissue, and penumbra zones, which is essential for determining the presence and boundaries of damaged brain tissue. Additionally, fractal analysis of intracerebral hemorrhages has shown that hemorrhage geometry is correlated with prognosis and survival rates. This method has been used to assess cortex and white matter configurations in stroke patients, highlighting brain remodeling and compensatory changes. It has also been proven effective in detecting morphological alterations in brain structures during transient ischemic attacks. Moreover, fractal analysis of the brain vasculature revealed changes associated with ischemic stroke and hemorrhage. Overall, the fractal analysis technique in brain magnetic resonance imaging and computed tomography is an informative and sensitive imaging analysis method that, with further development, can significantly improve stroke diagnosis and prognosis on the basis of neuroimaging data.
