"Machine Learning for Brain Disorders" is now published! 1058 pages fully open access

RT @FabianIsensee1: Excited to share nnInteractive: The nnU-Net moment for 3D Interactive Segmentation! Supports points, scribbles, boxes,….

Across MICCAI 2023 segmentation papers:. Median improvement over SOTA: 1 percent point of Dice. Median (imputed) Confidence Interval width: 3 percent points. Should we be worried? 😱. To learn more, see poster T-AM-065 by @evangelia_chris @annika_reinke1 at 10.30 #MICCAI2024.

RT @MeriBach: Back to #MICCAI2024 after some years is really exciting, great job of the team with posters and presentations. And it just st….

RT @MICCAI_Society: Welcome to #MICCAI2024! Today marks the beginning of an exciting series of workshops, challenges, and tutorials. We're….

RT @DKFZ_IMSY_lab: 🔥#MICCAI2024 Teaser 1🔥:. Can we trust our medical imaging AI results? . We analyzed all 221 MICCAI 2023 segmentation pap….

RT @DKFZ_IMSY_lab: … between @helmholtz_image the @MICCAI_Society SIG on challenges @bias_sig the @ProjectMONAI benchmarking group and inv….

RT @SashimiWorkshop: 🙌We are beyond excited to have the great @lena_maierhein as our keynote speaker at SASHIMI 2024! 🙌 #MICCAI2024. Keynot….

RT @MELBAJournal: 🚨 New publication alert:.📢 “Automated MRI Quality Assessment of Brain T1-weighted MRI in Clinical Data Warehouses: A Tran….

RT @Bernoulli_Lab: Découvrez le projet APPRIMAGE qui vise à valider à grande échelle une méthode d’apprentissage automatique pour l’aide au….

RT @chrisdav66: Happy to share this cross-diagnostic review paper on Dimensional Neuroimaging Endophenotypes: Neurobiological Representatio….

RT @MELBAJournal: 🚨 New publication alert:.📢 “Evaluation of pseudo-healthy image reconstruction for anomaly detection with deep generative….

RT @pfjaeger: In 2021, we published nnU-Net addressing an ongoing bias towards novel architectures in medical image segmentation. Now, 3 ye….

Merci à tous les collègues grenoblois pour l'organisation de cette magnifique nouvelle édition d'IABM ! En particulier @benlemasson @MichelDojat @MIAI_UGA.

Finally, do not hesitate to contact us by email if you are looking for a PhD thesis: we have two PhD thesis positions in AI for medical imaging, one based in Paris and one based in Lille!. More info about the labs: and (n/n).

Grateful to:.- Inserm/Institut pour la Recherche en Santé Publique for their support.- all our partners and look forward to working together!.- our former/current PhD candidates @SimonaBottani and @loizillon_s whose outstanding work has laid the foundations for this project.

- the Entrepôt de Données de Santé of AP-HP, Assistance Publique - Hôpitaux de Paris, with the pôle I&D (Martin HILKA, Stephane BREANT Aurélien Maire Yannick Jacob). - the Entrepôt de Données de Santé INCLUDE at CHU de Lille (Grégoire Ficheur Charlotte Ferran). 6/n.

- the Department of Neuroradiology at Pitié-Salpêtrière AP-HP, Assistance Publique - Hôpitaux de Paris (Stéphane Lehéricy, Nadya Pyatigorskaya, Lydia Chougar). - the Department of Neuroradiology at CHU de Lille (Grégory Kuchcinski Martin Bretzner Jean-Pierre Pruvo).

Our consortium gathers:.- the @AramisLabParis at @InstitutCerveau @CNRS @Inserm @Sorbonne_Univ_ @inria_paris @InstitutPrairie (@NinonBurgos and myself). - the Lille Neuroscience and Cognition unit at Universite de Lille @Inserm CHU Lille (@RenaudLopes Cécile Bordier). 4/n.

We will build the tools needed to harness this unique source of real-world medical data: . - develop AI tools for automatic quality assurance and harmonization. - make these tools available to the community. - use them to build a PoC AI-assisted reading system for neuroradiology.

Clinical data warehouses gather data from millions of patients, they offer fantastic opportunities for research but their use raises major challenges, among which data quality and heterogeneity have been flagged as critical by the @HAS_sante . 2/n.