Editorial

摘要

Deep learning methods have experienced an immense growth in interest from the medical image analysis community, particularly in the last years. The main reasons behind this interest lie in ability of deep learning algorithms to process very large training sets, to transfer learned features between different databases, and to analyse multimodal data. These advantages are providing important opportunities for the development of medical image analysis methodologies, such as computer-aided diagnosis, image segmentation, image annotation and retrieval, image registration and multimodal image analysis. Deep Learning in Medical Image Analysis (DLMIA) is a workshop dedicated to the presentation of works focused on the design and use of deep learning methods in medical image analysis applications. This workshop is setting the trends and identifying the challenges of the use of deep learning methods in medical image analysis. Another important objective of the workshop is to continue and increase the connection between software developers, specialist researchers and applied end-users from diverse fields related to Medical Image and Signal Processing, which are the main scopes of the International Conference On Medical Image Computing & Computer Assisted Intervention (MICCAI).