The MIDL conference aims to be a forum for deep learning researchers, clinicians and health-care companies to take a leap in the application of deep learning based automatic image analysis in disease screening, diagnosis, prognosis, treatment selection and treatment monitoring.
+Dates
Paper registration deadline 24 January 2020
Paper submission deadline 30 January 2020
Conference dates 4-6 July 2020
+Aim and Scope
We welcome submissions, as full or short papers, for the 3rd International Conference on Medical Imaging with Deep Learning. This conference is a forum for deep learning researchers, clinicians and health-care companies working at the intersection of medical image analysis and machine learning for disease detection, diagnosis, prognosis, intervention, treatment selection and monitoring of disease progression.
The conference has a broad scope including all areas of medical image analysis and computer-assisted intervention where deep learning is a key element.
Topics of interest include but are not limited to:
-Semantic segmentation of medical images
-Learning based image registration
-Computer-aided detection and diagnosis
-Image acquisition, reconstruction and synthesis
-Transfer learning and domain adaptation
-Learning with noisy labels and limited data
-Unsupervised deep learning and representation learning
-Uncertainty estimation for medical diagnosis
-Interpretability and explainable deep learning
-Integration of imaging and clinical data
-Validation studies and deep learning applications in radiology, pathology, endoscopy, dermatology, ophthalmology, and beyond
Conference submissions follow two tracks: full conference papers and short papers. Full papers contain well-validated applications or methodological developments of deep learning algorithms in medical imaging. There is no strict limit on paper length. However, we strongly recommend keeping the paper at 8 pages, plus 1 page for the references and as many pages as needed in an appendix section (all in a single pdf).
All accepted papers are made free to read after the conference without paywalls. Reviewing will be performed using OpenReview.
November 26th, 2019 
Daniela Lopez de Luise 
