Fractal Dimension

Fractal dimension (FD), a measure of a pattern's complexity across different scales, is being increasingly applied to analyze diverse systems exhibiting self-similarity. Current research focuses on leveraging FD in machine learning models, particularly for improved image segmentation and prediction tasks (e.g., aneurysm rupture risk, driver cognition), often integrating FD features into deep learning architectures like U-Nets. These applications highlight FD's potential to enhance the accuracy and efficiency of various algorithms, while ongoing investigations explore its limitations as a predictor of model generalization and its relationship to other complexity measures.