Визначення онкології за допомогою фрактального аналізу

Abstract

Fractal analysis is an emerging quantitative method in oncology that enables objective characterization of tumor morphology through the calculation of fractal dimension (FD). Unlike traditional qualitative histopathological assessment, fractal-based approaches provide reproducible numerical metrics that correlate with malignancy grade, tissue heterogeneity, and treatment response. This paper reviews the application of fractal geometry in cancer diagnostics, including histopathology, MRI-based radiomics, and automated classification systems enhanced by machine learning. Studies demonstrate that FD can differentiate benign from malignant lesions with high specificity, predict pathological complete response to neoadjuvant chemotherapy, and reflect tumor immune microenvironment characteristics. The integration of fractal analysis with modern imaging modalities represents a promising direction for non-invasive, data-driven oncological diagnostics.