Special issue: 4th MICCAI workshop on deep learning in medical image analysis

摘要

Deep-learning-based solutions have experienced a massive interest from the medical image analysis community. The main reasons behind this attention lie in the ability of such solutions to process huge training datasets, to transfer learned features between databases, and to taking into account multi-modal data. These advantages are providing important opportunities for the development of more competent medical image analysis systems, such as for computer-aided diagnosis, planning, intervention and follow-up. Deep Learning in Medical Image Analysis (DLMIA) is a workshop, organised since 2015 under the scope of the International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI), dedicated to the discussing of works focused on the design and use of deep learning methods in medical image analysis applications. Since its first edition, 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 and Machine Learning.