Fractal Analysis of Medical Images to Diagnose Brain Tumors
Authors: Joshita Kamalakannan, Galilee Samuels, Katherine Penullar
Faculty Supervisor: Ilmi Yoon
Department: Computer Science
This research aims to apply new machine learning features towards the detection of brain tumors in medical images using the Brain Tumor Segmentation (BraTS) dataset. Fractal analysis is a mathematical technique that quantifies and analyzes patterns and structures. Exploration with fractal analysis will discern intricate patterns indicative of brain tumor presence from the medical images to extract features for machine learning from the dataset. Use of the brain tumor dataset is motivated by the availability of current existing algorithms, machine learning techniques and libraries designed for cancer detection in medical images. With the application of fractal analysis, the research seeks to explore what could potentially be a powerful technique for machine learning prediction in medical imaging analysis.