Files

Abstract

The goal of this project was to evaluate the feasibility of machine learning methods based on feature extraction and classification for differentiating benign and malignant prostate cancer tumors in mp-MRI with the intent of building an algorithm that best reduces over-biopsy and enables in-silico biopsy. The specific aim of this project was to evaluate various extracted texture features, dimensionality reduction, and machine learning classification methods to determine the computer-aided analysis model that provides the greatest classification accuracy for malignant and benign prostate cancer images.

Details

PDF

Statistics

from
to
Export
Download Full History