Introducing QuantConn: Overcoming Challenging Diffusion Acquisitions with Harmonization. - Nancy Newlin; Kurt Schilling; Serge Koudoro; Bramsh Qamar Chandio; Praitayini Kanakaraj; Daniel Moyer; Claire E. Kelly; Sila Genc; Joseph Yuan-Mou Yang; Ye Wu 001; Nagesh Adluru; Vishwesh Nath; et al. (CDMRI@MICCAI, 2024)

Yucca: A Deep Learning Framework For Medical Image Analysis. - Sebastian Nørgaard Llambias; Julia Machnio; Asbjørn Munk; Jakob Ambsdorf; Mads Nielsen; Mostafa Mehdipour-Ghazi (CoRR, 2024)

MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI. - Nancy R. Newlin; Kurt Schilling; Serge Koudoro; Bramsh Qamar Chandio; Praitayini Kanakaraj; Daniel Moyer; Claire E. Kelly; Sila Genc; Jian Chen; Joseph Yuan-Mou Yang; Ye Wu; Yifei He; et al. (CoRR, 2024)

Deep Learning for Localization of White Matter Lesions in Neurological Diseases. - Julia Machnio; Mads Nielsen; Mostafa Mehdipour-Ghazi (NLDL, 2025)

A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learning. - Asbjørn Munk; Stefano Cerri; Jakob Ambsdorf; Julia Machnio; Sebastian Nørgaard Llambias; Vardan Nersesjan; Christian Hedeager Krag; Peirong Liu; Pablo Rocamora-García; Mostafa Mehdipour-Ghazi; Mikael Boesen; Michael Eriksen Benros; et al. (CoRR, 2025)

Towards Scalable and Robust White Matter Lesion Localization via Multimodal Deep Learning. - Julia Machnio; Sebastian Nørgaard Llambias; Mads Nielsen; Mostafa Mehdipour-Ghazi (CoRR, 2025)

To Label or Not to Label: PALM - A Predictive Model for Evaluating Sample Efficiency in Active Learning Models. - Julia Machnio; Mads Nielsen; Mostafa Mehdipour-Ghazi (CoRR, 2025)