Machine learning plays an essential role in the medical imaging field, including computer-aided diagnosis, image segmentation, image registration, image fusion, image-guided therapy, image annotation and image database retrieval. Machine Learning in Medical Imaging (MLMI 2020) is the 11th in a series of workshops on this topic in conjunction with MICCAI 2020, will be held on Oct. 4 2020 as a fully virtual workshop. This workshop focuses on major trends and challenges in this area, and it presents original work aimed to identify new cutting-edge techniques and their applications in medical imaging.
- MLMI 2020 will go 100% virtual.
- Accepted papers will be published in LNCS proceeding.
- MLMI 2020 Best Paper Award will be presented to the best overall scientific paper.
Our goal is to advance scientific research within the broad field of machine learning in medical imaging. The technical program will consist of previously unpublished, contributed papers, with substantial time allocated to discussion. We are looking for original, high-quality submissions on innovative researches and developments in medical image analysis using machine learning techniques.
Topics of interests include but are not limited to machine learning methods (e.g., statistical methods, deep learning, weakly supervised learning, reinforcement learning, extreme learning machines, etc) with their applications to (but not limited) the following areas:
- Image analysis of anatomical structures and lesions
- Computer-aided detection/diagnosis
- Multi-modality fusion for diagnosis, image analysis, and image-guided interventions
- Medical image reconstruction
- Medical image retrieval
- Cellular image analysis
- Molecular/pathologic image analysis
- Dynamic, functional, and physiologic imaging