Exploratory Matrix Factorization for PET Image Analysis

摘要

Features are extracted from PET images employing exploratory matrix factorization techniques, here non-negative matrix factorization (NMF). Appropriate features are fed into classifiers such as support vector machine or random forest. An automatic classification is achieved with high classification rate and only few false negatives.