Julia Machnio

According to our database, Julia Machnio authored at least 7 papers between 2024 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, July, 2025

Towards Scalable and Robust White Matter Lesion Localization via Multimodal Deep Learning.

Julia Machnio, Sebastian Nørgaard Llambias, Mads Nielsen, Mostafa Mehdipour-Ghazi

CoRR, June, 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, Juan Eugenio Iglesias, Mads Nielsen

CoRR, June, 2025

Deep Learning for Localization of White Matter Lesions in Neurological Diseases.

Julia Machnio, Mads Nielsen, Mostafa Mehdipour-Ghazi

Proceedings of the Northern Lights Deep Learning Conference, 2025

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, Jiawei Zhang, Qingrun Zeng, Fan Zhang, Nagesh Adluru, Vishwesh Nath, Sudhir K. Pathak, Walter Schneider, Anurag Gade, Yogesh Rathi, Tom Hendriks, Anna Vilanova, Maxime Chamberland, Tomasz Pieciak, Dominika Ciupek, Antonio Tristán-Vega, Santiago Aja-Fernández, Maciej Malawski, Gani Ouedraogo, Julia Machnio, Christian Ewert, Paul M. Thompson, Neda Jahanshad, Eleftherios Garyfallidis, Bennett A. Landman

CoRR, 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

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, Nagesh Adluru, Vishwesh Nath, Sudhir K. Pathak, Walter Schneider, Anurag Gade, William Consagra, Yogesh Rathi, Tom Hendriks, Anna Vilanova, Maxime Chamberland, Tomasz Pieciak, Dominika Ciupek, Antonio Tristán-Vega, Santiago Aja-Fernández, Maciej Malawski, Gani Ouedraogo, Julia Machnio, Paul M. Thompson, Neda Jahanshad, Eleftherios Garyfallidis, Bennett A. Landman

Proceedings of the Computational Diffusion MRI - 15th International Workshop, 2024