179 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of Eastern FinlandFI4 papers
- InsermFR2 papers
- National University Hospital of IcelandIS2 papers
- Aristotle University of ThessalonikiGR1 paper
- Berenson Allen Center for Noninvasive Brain StimulationUS1 paper
- Beth Israel Deaconess Medical CenterUS1 paper
- Biomedical Research Networking Center on Neurodegenerative DiseasesES1 paper
- Center for Neuroscience and Cognitive SystemsIT1 paper
- Central European Institute of TechnologyCZ1 paper
- Central European Institute of Technology – Masaryk UniversityCZ1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- Centro San Giovanni di Dio FatebenefratelliIT1 paper
5 papers
Dual-Input Dynamic Convolution for Positron Range Correction in PET Image Reconstruction
Youness Mellak, Alexandre Bousse, Thibaut Merlin +3
Positron range (PR) blurring degrades positron emission tomography (PET) image resolution, particularly for high-energy emitters like gallium-68 (68 Ga). We introduce Dual-Input Dy…
TMS-EEG Reliability: Bridging the Gap to Clinical Use
Giacomo Bertazzoli, Carlo Miniussi, Petro Julkunen +1
Concurrent transcranial magnetic stimulation (TMS) and electroencephalography (EEG), or TMS-EEG, holds the potential to broaden the clinical applications of TMS beyond its traditio…
aSAGA: Automatic Sleep Analysis with Gray Areas
Matias Rusanen, Gabriel Jouan, Riku Huttunen +10
State-of-the-art automatic sleep staging methods have already demonstrated comparable reliability and superior time efficiency to manual sleep staging. However, fully automatic bla…
MAMAF-Net: Motion-Aware and Multi-Attention Fusion Network for Stroke Diagnosis
Aysen Degerli, Pekka Jakala, Juha Pajula +2
Stroke is a major cause of mortality and disability worldwide from which one in four people are in danger of incurring in their lifetime. The pre-hospital stroke assessment plays a…
The reliability of a deep learning model in clinical out-of-distribution MRI data: a multicohort study
Gustav Mårtensson, Daniel Ferreira, Tobias Granberg +22
Deep learning (DL) methods have in recent years yielded impressive results in medical imaging, with the potential to function as clinical aid to radiologists. However, DL models in…