Author Instructions


Submission Instructions

MIDL 2023 submissions follow two tracks: full and short papers. All accepted full papers will be published as a volume in the Proceedings of Machine Learning Research. We will be using openreview.net as a submission and reviewing platform.

Full papers contain methodological developments or well-validated applications of deep learning algorithms in medical imaging. The paper length is limited to 8 pages excluding references and appendix sections. There is no page limit for the references and appendices, but reviewers are not obliged to evaluate any content included in an appendix section. The papers will go through a full, double-blind reviewing process via OpenReview. A selection of full papers will be invited for oral presentation. All accepted full papers will be published in the Proceedings of Machine Learning Research.

Short papers are strictly limited to 3 pages (including references) and can, for example, focus on novel methodological ideas without extensive validation. We also specifically accept short papers discussing recently published or submitted journal contributions to give authors the opportunity to present their work and obtain feedback from conference attendees. Selection of short papers is based on a light single-blind review process via OpenReview. All accepted short papers will be presented at the conference.

To submit a paper, authors need to have an updated OpenReview account.

The link will be posted at this location when submission opens.

Inquiries to the program chairs can be addressed directly to [email protected].

Paper registration

To be able to upload the PDF of a full or short paper before the submission deadlines, authors have to create a submission on openreview with title, abstract and author information a week in advance (paper registration deadline, 8 January 2023).

Latex template

To prepare your submission to MIDL 2023 either as a full or short paper, please use the LaTeX style files provided at: https://github.com/MIDL-Conference/MIDLLatexTemplate. Please use the anonymized variant of the template when submitting for review.


Dual submission policy

Full papers

Submissions that are substantially similar to papers that have been previously published, or accepted for publication, or that are submitted in parallel to other conferences with proceedings or journals, are not allowed.

Short papers

In addition to original work, authors can choose to submit a shortened version of a recently published, or submitted, journal publication to foster dissemination of high-quality work. Submissions that are substantially similar to versions that have been accepted or submitted in parallel to other conferences with proceedings are not allowed.

In both cases, dual submission of your paper to a non-peer reviewed website like arXiv is allowed. Similarly, submissions that have been presented at non-archival workshops (i.e., venues that do not have publication proceedings or publish only a very short abstract) do not violate the policy.

This policy will be enforced during the whole reviewing process period.