Papers in Journals

Lara Dular, Žiga Špiclin

BASE: brain age standardized evaluation

NeuroImage, 285:120469, 2024

JCR Impact Factor: 5.7 (2022) -- Best Category: 1/14 neuroimaging -- Quartile: 1

• doi:10.1016/j.neuroimage.2023.120469
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Papers in Journals

Lara Dular, Franjo Pernuš, Žiga Špiclin

Extensive T1-weighted MRI preprocessing improves generalizability of deep brain age prediction models

Computers in Biology and Medicine, 173:108320, 2024

JCR Impact Factor: 7.7 (2022) -- Best Category: 4/55 mathematical & computational biology -- Quartile: 1

• doi:10.1016/j.compbiomed.2024.108320
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Papers in Journals

Lara Dular, Gregor Brecl Jakob, Lina Savšek, Jožef Magdič, Bojan Rojc, Žiga Špiclin

Napovedovanje kliničnega poteka multiple skleroze iz magnetnoresonančnih slik: predhodni rezultati raziskave

Medicinski razgledi, 62(suppl. 1):51-57, 2023

• https://medrazgl.si/
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Papers in Conference Proceedings

Lara Dular, Gregor Brecl-Jakob, Lina Savšek, Jožef Magdič, Žiga Špiclin

Predicting future multiple sclerosis disease progression from MR scans

SPIE Medical Imaging 2023: Image Processing, Feb 19-23, San Diego, CA, USA (I. Išgum, O. Colliot, Eds.), 12465:124652U, 2023

• doi:10.1117/12.2654416
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Abstracts in Conference Proceedings

Lara Dular, Domen Preložnik, Gregor Brecl Jakob, Lina Savšek, Jožef Magdič, Bojan Rojc, Žiga Špiclin

Future MS disease progression prediction using deep learning on conventional MRI scans

ACTRIMS Forum 2023, Feb 23-25, San Diego, USA, Multiple Scleroris Journal 29(Suppl 2):151, 2023

• doi:10.1177/13524585231169437
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Abstracts in Conference Proceedings

Lara Dular, Gregor Brecl Jakob, Lina Savšek, Jožef Magdič, Bojan Rojc, Žiga Špiclin

Prediction of future disease progression from magnetic resonance images using brain and lesion volumetry and lesion-induced tract disconnectivity

9th Joint ECTRIMS-ACTRIMS meeting - MSMilan2023, Oct 11-13, Milan, Italy, Multiple Scleroris Journal 29(Suppl 3):323-324, 2023

• doi:10.1177/13524585231196192
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Papers in Conference Proceedings

Lara Dular, Žiga Špiclin

Mixup augmentation improves age prediction from T1-weighted brain MRI scans

5th International Workshop on Predictive Intelligence in Medicine - MICCAI-PRIME 2022, Sep 20, Singapore (I. Rekik et al., Eds.), Lecture Notes in Computer Science 13564:60-70, 2022

• doi:10.1007/978-3-031-16919-9_6
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Papers in Conference Proceedings

Martin Žukovec, Lara Dular, Žiga Špiclin

Modeling multi-annotator uncertainty as multi-class segmentation problem

7th BrainLes International Workshop, held in conjunction with the 24th International Conference on Medical Image Computing and Computer Assisted Intervention - MICCAI 2021, Sep 27, Strasbourg, France (A. Crimi, S. Bakas, Eds.), Lecture Notes in Computer Science 12962:112-123, 2022

• doi:10.1007/978-3-031-08999-2_9
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Papers in Conference Proceedings

Lara Dular, Žiga Špiclin

Improving across dataset brain age predictions using transfer learning

4th International Workshop on Predictive Intelligence in Medicine - MICCAI-PRIME 2021, Oct 1, Strasbourg, France (I. Rekik et al., Eds.), Lecture Notes in Computer Science 12928:243-254, 2021

• doi:10.1007/978-3-030-87602-9_23
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Abstracts in Conference Proceedings

Lara Dular, Žiga Špiclin

Deep learning models for brain age estimation

Computational Approaches for Ageing and Age-Related Diseases - CompAge 2020, Sep 1-2, Paris, France, 2020

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