Unsupervised abnormality detection through mixed structure regularization (MSR) in deep sparse autoencoders.
Journal:
Medical physics
Published Date:
Mar 22, 2019
Abstract
PURPOSE: The purpose of this study is to introduce and evaluate the mixed structure regularization (MSR) approach for a deep sparse autoencoder aimed at unsupervised abnormality detection in medical images. Unsupervised abnormality detection based on identifying outliers using deep sparse autoencoders is a very appealing approach for computer-aided detection systems as it requires only healthy data for training rather than expert annotated abnormality. However, regularization is required to avoid overfitting of the network to the training data.