Unsupervised pathology detection in medical images using conditional variational autoencoders.
Journal:
International journal of computer assisted radiology and surgery
Published Date:
Dec 12, 2018
Abstract
PURPOSE: Pathology detection in medical image data is an important but a rather complicated task. In particular, the big variability of the pathologies is a challenge to automatic detection methods and even to machine learning methods. Supervised algorithms would usually learn the appearance of a single pathological structure based on a large annotated dataset. As such data is not usually available, especially in large amounts, in this work we pursue a different unsupervised approach.