Go to DBLP homepagePreface for International Conference on Medical Imaging with Deep Learning 2024
Abstract: This volume contains the Proceedings of the Seventh International Conference on Medical Imaging with Deep Learning - MIDL 2024. The conference was held from July 3 to 5, 2024, in Paris, France and it was organized by co-chairs Ninon Burgos, Caroline Petitjean and Maria Vakalopoulou from Centre national de la recherche scientifique (CNRS) - Paris Brain Institute, University of Rouen Normandie and CentraleSupélec Université Paris Saclay, respectively. The scientific program was organized by a team of program chairs from CentraleSupelec, CNRS - LaBRI, Inria Sophia-Antipolis, CNRS - CREATIS and Centrale Nantes - LS2N. Similar to the previous editions of the conference, MIDL 2024 had two submission tracks: full papers and short papers. 181 valid full papers and 124 short papers underwent a transparent review process through the OpenReview platform. Both the full paper and short paper track review processes were single-blind. The papers and reviews are publicly available through OpenReview, the papers with a final decision of rejection were not listed in the OpenReview platform. The full paper submissions underwent a rigorous single-blind review process that involved a team of 5 Program Chairs (PC), 27 Area Chairs (AC), and 202 reviewers. For each submission at least 3 reviews were ensured. After desk rejection of incomplete submissions by PC, each of the remaining 217 papers received at least three reviews as well as a meta-review by an AC, and the authors were allowed to respond to the reviews during a rebuttal period. The PC then discussed each borderline paper over a virtual meeting to make the accept/reject decisions and to select oral presentations. The acceptance rate of the full paper track was $54 %$, with 36 oral presentations and 81 posters. The short paper submissions underwent a more streamlined single-blind review process involving a team of the same 5 PCs and 25 reviewers, most of whom had also served as AC for the full paper track. Of the 170 submissions, 105 were accepted as posters. We want to thank the Area Chairs and reviewers for their careful reviews and constructive feedback to the authors, which made it possible to create this robust technical program. We are grateful to our sponsors for their financial support of the conference. Finally, we would also like to thank the OpenReview team for their tech support throughout the entire process. The articles in these proceedings are presented in alphabetical order by first author surnames. The papers consist of a wide range of topics including segmentation, representation learning, multimodal methods, semi/weakly-supervised learning, clinical translation & domain adaptation, geometric deep learning, federated learning, synthesis, explainable AI, uncertainty and foundation models. *Paris, September 25, 2024*
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