Žiga Špiclin

发表

Validation of White-Matter Lesion Change Detection Methods on a Novel Publicly Available MRI Image Database

F. Pernus, B. Likar, Ž. Špiclin, 2016, Neuroinformatics.

A Novel Public MR Image Dataset of Multiple Sclerosis Patients With Lesion Segmentations Based on Multi-rater Consensus

Bostjan Likar, Franjo Pernus, Ziga Spiclin, 2017, Neuroinformatics.

Beyond Frangi: an improved multiscale vesselness filter

Bostjan Likar, Franjo Pernus, Ziga Spiclin, 2015, Medical Imaging.

A framework for automatic creation of gold-standard rigid 3D–2D registration datasets

Bostjan Likar, Franjo Pernus, Ziga Spiclin, 2017, International Journal of Computer Assisted Radiology and Surgery.

Device and methods for "gold standard" registration of clinical 3D and 2D cerebral angiograms

Bostjan Likar, Franjo Pernus, Ziga Spiclin, 2015, Medical Imaging.

Robust Estimation of Unbalanced Mixture Models on Samples with Outliers

Bostjan Likar, Franjo Pernus, Ziga Spiclin, 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

IMPACT OF AEROBIC EXERCISE ON CLINICAL AND MAGNETIC RESONANCE IMAGING BIOMARKERS IN PERSONS WITH MULTIPLE SCLEROSIS: AN EXPLORATORY RANDOMIZED CONTROLLED TRIAL

V. Strojnik, A. Ihan, L. Savšek, 2021, Journal of rehabilitation medicine.

Automated Cutting Plane Positioning for Intracranial Aneurysm Quantification

Bostjan Likar, Franjo Pernus, Ziga Spiclin, 2020, IEEE Transactions on Biomedical Engineering.

Automatic cutting plane identification for computer-aided analysis of intracranial aneurysms

Bostjan Likar, Franjo Pernus, Ziga Spiclin, 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).

Computer-Aided Detection and Quantification of Intracranial Aneurysms

Bostjan Likar, Franjo Pernus, Ziga Spiclin, 2015, MICCAI.

Detection and Localization of Hyperfunctioning Parathyroid Glands on [18F]fluorocholine PET/ CT Using Deep Learning – Model Performance and Comparison to Human Experts

M. Hočevar, M. Jensterle, S. Rep, 2022, Radiology and oncology.

Predicting future multiple sclerosis disease progression from MR scans

L. Savšek, Ž. Špiclin, J. Magdič, 2023, Medical Imaging.

Spatio-temporal Learning from Longitudinal Data for Multiple Sclerosis Lesion Segmentation pdf

Ziga Spiclin, Nassir Navab, Seong Tae Kim, 2020, BrainLes@MICCAI.

Automatic Detection of Misalignment in Rigid 3D-2D Registration

Uros Mitrovic, Bostjan Likar, Franjo Pernus, 2013, CLIP.

Blob Enhancement and Visualization for Improved Intracranial Aneurysm Detection

Bostjan Likar, Franjo Pernus, Ziga Spiclin, 2016, IEEE Transactions on Visualization and Computer Graphics.

Enhancement of Vascular Structures in 3D and 2D Angiographic Images

F. Pernus, B. Likar, T. Jerman, 2016, IEEE Transactions on Medical Imaging.

Vascular Surface Segmentation for Intracranial Aneurysm Isolation and Quantification

Bostjan Likar, Franjo Pernus, Ziga Spiclin, 2020, MICCAI.

Stratified mixture modeling for segmentation of white-matter lesions in brain MR images

Bostjan Likar, Franjo Pernus, Ziga Spiclin, 2016, NeuroImage.

BASE: Brain Age Standardized Evaluation

Alzheimer's Disease Neuroimaging Initiative, Lara Dular, Žiga Špiclin, 2023, NeuroImage.

Psychometric evaluation of the 5-item Medication Adherence Report Scale questionnaire in persons with multiple sclerosis

U. Rot, L. Savšek, G. Brecl Jakob, 2024, PloS one.

Geometric calibration of a hyperspectral imaging system.

Bostjan Likar, Franjo Pernus, Miran Bürmen, 2010, Applied optics.

Extensive T1-weighted MRI Preprocessing Improves Generalizability of Deep Brain Age Prediction Models

F. Pernus, Lara Dular, Žiga Špiclin, 2023, bioRxiv.

Aneurysm growth evaluation and detection: a computer-assisted follow-up MRA analysis

Žiga Špiclin, Žiga Bizjak, 2024, Scientific reports.

Assessing accuracy and consistency in intracranial aneurysm sizing: human expertise vs. artificial intelligence

Žiga Špiclin, Žiga Bizjak, Andrej Planinc, 2024, Scientific reports.

Locally adaptive magnetic resonance intensity models for unsupervised segmentation of multiple sclerosis lesions

Boštjan Likar, Franjo Pernuš, Daniel L Rubin, 2017, Journal of medical imaging.

Locally adaptive MR intensity models and MRF-based segmentation of multiple sclerosis lesions

Bostjan Likar, Franjo Pernus, Ziga Spiclin, 2015, Medical Imaging.

Automated segmentation of MS lesions in brain MR images using localized trimmed-likelihood estimation

Bostjan Likar, Franjo Pernus, Ziga Spiclin, 2013, Medical Imaging.

Deep shape based intracranial aneurysm rupture prediction

W. Park, Jannik Sobisch, Žiga Špiclin, 2024, Medical Imaging.

Deep geometric learning for intracranial aneurysm detection: towards expert rater performance

F. Pernus, W. Park, Žiga Špiclin, 2023, Journal of neurointerventional surgery.

Analysis of Brain Age Gap across Subject Cohorts and Prediction Model Architectures

Lara Dular, Žiga Špiclin, 2024, Biomedicines.