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Neuroimage
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December 8, 2023
BASE: Brain Age Standardized Evaluation
Lara Dular, Žiga Špiclin,
Biomedicines
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November 25, 2023
A Systematic Review of Deep-Learning Methods for Intracranial Aneurysm Detection in CT Angiography
Žiga Bizjak, Žiga Špiclin
Scientific Reports
|
August 23, 2024
Aneurysm growth evaluation and detection: a computer-assisted follow-up MRA analysis
Žiga Bizjak, Žiga Špiclin
Statistical Methods in Medical Research
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February 1, 2018
Reference-free error estimation for multiple measurement methods
Hennadii Madan, Franjo Pernuš, Žiga Špiclin
Biorxiv : the Preprint Server for Biology
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May 22, 2023
Extensive T1-weighted MRI Preprocessing Improves Generalizability of Deep Brain Age Prediction Models
Lara Dular, Franjo Pernuš, Žiga Špiclin
Frontiers in Physiology
|
July 19, 2021
Deep Shape Features for Predicting Future Intracranial Aneurysm Growth
Žiga Bizjak, Franjo Pernuš, Žiga Špiclin
Computers in Biology and Medicine
|
March 26, 2024
Extensive T1-weighted MRI preprocessing improves generalizability of deep brain age prediction models
Lara Dular, Franjo Pernuš, Žiga Špiclin, et al.
IEEE Transactions on Medical Imaging
|
May 8, 2013
3D-2D registration of cerebral angiograms: a method and evaluation on clinical images
Uroš Mitrovic, Žiga Špiclin, Boštjan Likar, et al.
Proceedings of Machine Learning Research
|
April 20, 2023
Automated intracranial vessel labeling with learning boosted by vessel connectivity, radii and spatial context
Jannik Sobisch, Žiga Bizjak, Aichi Chien, et al.
Medical Physics
|
November 2, 2015
Simultaneous 3D-2D image registration and C-arm calibration: Application to endovascular image-guided interventions
Uroš Mitrović, Franjo Pernuš, Boštjan Likar, et al.
Page
of 3
Search research articles
Search
Showing results (1-10 of 26) with videos related to
Sort By:
Page
of 3
Neuroimage
|
December 8, 2023
BASE: Brain Age Standardized Evaluation
Lara Dular, Žiga Špiclin,
Biomedicines
|
November 25, 2023
A Systematic Review of Deep-Learning Methods for Intracranial Aneurysm Detection in CT Angiography
Žiga Bizjak, Žiga Špiclin
Scientific Reports
|
August 23, 2024
Aneurysm growth evaluation and detection: a computer-assisted follow-up MRA analysis
Žiga Bizjak, Žiga Špiclin
Statistical Methods in Medical Research
|
February 1, 2018
Reference-free error estimation for multiple measurement methods
Hennadii Madan, Franjo Pernuš, Žiga Špiclin
Biorxiv : the Preprint Server for Biology
|
May 22, 2023
Extensive T1-weighted MRI Preprocessing Improves Generalizability of Deep Brain Age Prediction Models
Lara Dular, Franjo Pernuš, Žiga Špiclin
Frontiers in Physiology
|
July 19, 2021
Deep Shape Features for Predicting Future Intracranial Aneurysm Growth
Žiga Bizjak, Franjo Pernuš, Žiga Špiclin
Computers in Biology and Medicine
|
March 26, 2024
Extensive T1-weighted MRI preprocessing improves generalizability of deep brain age prediction models
Lara Dular, Franjo Pernuš, Žiga Špiclin, et al.
IEEE Transactions on Medical Imaging
|
May 8, 2013
3D-2D registration of cerebral angiograms: a method and evaluation on clinical images
Uroš Mitrovic, Žiga Špiclin, Boštjan Likar, et al.
Proceedings of Machine Learning Research
|
April 20, 2023
Automated intracranial vessel labeling with learning boosted by vessel connectivity, radii and spatial context
Jannik Sobisch, Žiga Bizjak, Aichi Chien, et al.
Medical Physics
|
November 2, 2015
Simultaneous 3D-2D image registration and C-arm calibration: Application to endovascular image-guided interventions
Uroš Mitrović, Franjo Pernuš, Boštjan Likar, et al.
Page
of 3