🚨 New publication alert:
📢 “Automated MRI Quality Assessment of Brain T1-weighted MRI in Clinical Data Warehouses: A Transfer Learning Approach Relying on Artefact Simulation.”
🖊️ @loizillon_s, S. Bottani, S. Mabille, Y. Jacob, ... , @oliviercolliot, @NinonBurgos et al.
⬇️
New preprint - Reproducibility in medical image computing
https://t.co/lV69pxpwMH
➡️ What is it?
➡️How is it assessed? In particular, we analyzed reproducibility reviews from MICCAI 2023 @MICCAI_Society
with @NinonBurgos E. Thibeau-Sutre and C. Brianceau
A thread 🧵
(1/n)
ML for brain disorders: one chapter / day
EEG and MEG are cornerstone modalities in brain disorders! They allow to measure evoked activity, oscillations, functional connectivity…
Chapter by @MConstanceCorsi@AramisLabParis
https://t.co/rehOXcZPGl
Check out the latest version of ClinicaDL 🐙. Many new features have been added:
🧠 New modality supported,
🚀 New data augmentation tools,
🔝 Better support of VAE,
🔧 Full refactoring of tsvtools,
And more ...👇
https://t.co/r67397rauZ
@AramisLabParis@ParisBrainInst
Happy to share the creation of Brainetics an **international associate team** between @AramisLabParis and @PCTGenomics to foster the ongoing collaboration between the teams an facilitate student mobility (@inria_paris and @IMBatUQ)
https://t.co/0iA86fUzS7
🤖L'intelligence artificielle au service du diagnostic des maladies neurodégénératives : "l'algorithme sera capable de dire si l'image qu'on lui soumet est celle d'un sujet sain ou d'un patient", Ninon Burgos, chercheuse @CNRS à l'@InstitutCerveau.
@LCP
https://t.co/aChZwEllhl