Aim and Scope
The conference program will include keynote presentations from invited speakers, oral presentations, posters and live demonstrations of deep learning algorithms from academia and industry.
We invite submissions on all topics related to medical imaging using deep learning. Topics discussed will include, but are not limited to:
- Semantic segmentation of medical images
- (Multi-modal) image registration with deep learning
- Interventional image analysis with deep learning (e.g. endoscopic imaging, image-guided surgery)
- Computer-aided detection and diagnosis
- Image synthesis and reconstruction
- Transfer learning for medical imaging
- Multi-dimensional algorithms (3D, 4D and beyond)
- Learning with noisy labels
- Learning with sparse data/labels
- Unsupervised deep learning
- Uncertainty estimation
- Integration of imaging and clinical data
- Data augmentation for medical images
- End-to-end learning for prognosis and treatment selection
- Thorough evaluation studies demonstrating application of deep learning algorithms
Conference submissions follow two tracks: full conference papers (conference track) and extended abstracts (abstract track). Both tracks will have the same deadline on April 11th, 2018. Submissions will be considered non-archival and can be submitted elsewhere after the conference. You are free to post your paper at arXiv or another preprint server.
Further information can be found in the submission guidelines.
MIDL Special Issue in Medical Image Analysis
We are happy that Medical Image Analysis, a top journal in the field, has agreed to publish a Special Issue based on contributions to MIDL. The best accepted full conference papers will be invited for submission to this special issue. Authors of the selected papers will be given the option to extend their original submissions with supplementary material. More information including deadlines for the special issue is available here.