arXiv:2609.06807v1 Announce Type: cross
Abstract: In this work, we comprehensively evaluate three popular feature-extraction paradigms in AI-based neuroimaging modeling: (1) computation of anatomical...
By Boyang Yu, Miquel Lopez Escoriza, Long Chen, Arjun V. Masurkar, Narges Razavian, Carlos Fernandez-Granda
The paper presents a systematic comparison of recurrent neural networks and Transformer models for iterative diffusion MRI tractography, focusing on training strategies, input representations, and hyperparameter tuning. It introduces a generation‑validation phase that provides streamline‑level supervision, enabling the models to achieve the best performance reported on the ISMRM2015 challenge dataset. The study also evaluates the effects of missing bundles, noisy training data, and invalid fibers, and demonstrates applicability to in‑vivo data from the Tractoinferno database.
By Emmanuelle Renauld, Philippe Poulin, Hugo Larochelle, Antoine Th\'eberge, Maxime Descoteaux
Machine learning (ML) has emerged as a promising approach for improving diffusion MRI (dMRI) tractography, a task that remains limited by the intrinsic tension between local diffusion information and...
The study evaluated a pragmatic deep‑learning approach for segmenting acute ischemic stroke lesions on diffusion‑weighted MRI. Using a self‑configured nnU‑Net trained on 1,744 cases and tested on 436, the baseline model achieved a median Dice similarity coefficient of 0.84, outperforming the DeepISLES ensemble, especially for smaller infarcts. The approach required minimal preprocessing and fast inference, suggesting it could streamline clinical stroke imaging workflows.
By Atle Bj{\o}rnerud, Till Schellhorn, Thor H. Skatt{\o}r, Terje Nome, Jon Andr\'e Ottesen, Anne Hege Aamodt, Bradley J MacIntosh
arXiv:2606. 15457v1 Announce Type: cross Abstract: 3D FLAIR MRI is widely recommended as one of the standard MRI sequences for brain imaging in multiple sclerosis (MS), but publicly available MS datasets remain relatively small and vary across scanners, acquisition protocols, and lesion patterns.
By Weidong Zhang, Yongchan Jung, Shafayat Mowla Anik, Furen Xiao, Vasudevan Janarthanan, Enkhzaya Chuluunbaatar, Byeong Kil Lee, Jeeho Ryoo
arXiv:2610.00279v1 Announce Type: new
Abstract: The segmentation of anatomical structures in medical images and particularly in MRI scans, is essential for clinical diagnosis and monitoring disease p...
By Eirini Cholopoulou, Dimitrios E. Diamantis, Dimitris K. Iakovidis