World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
9320
World Ranking
8683
National Ranking
8

Overview

Franjo Pernuš is affiliated with the University of Ljubljana in Slovenia. Their research primarily spans the field of Medicine, with a focus on Radiology, Nuclear Medicine and Imaging, Neurology, Pulmonary and Respiratory Medicine, Biomedical Engineering, and Pediatrics, Perinatology and Child Health.

The main topics covered in their work include:

  • Intracranial Aneurysms: Treatment and Complications
  • Cerebrovascular and Carotid Artery Diseases
  • Advanced Neuroimaging Techniques and Applications
  • Fetal and Pediatric Neurological Disorders
  • Optical Imaging and Spectroscopy Techniques
  • Photoacoustic and Ultrasonic Imaging
  • Retinal Imaging and Analysis

Franjo Pernuš has contributed to several publications across notable venues, including:

  • arXiv (Cornell University)
  • Medical Physics
  • Frontiers in Physiology
  • Computers in Biology and Medicine
  • Biomedical Optics Express

Among the recent papers authored or coauthored by Franjo Pernuš are:

  • Auto-segmentation of organs at risk for head and neck radiotherapy planning: From atlas-based to deep learning methods, 2020, Medical Physics
  • Deep Shape Features for Predicting Future Intracranial Aneurysm Growth, 2021, Frontiers in Physiology
  • Extensive T1-weighted MRI preprocessing improves generalizability of deep brain age prediction models, 2024, Computers in Biology and Medicine
  • Fast and accurate Monte Carlo simulations of subdiffusive spatially resolved reflectance for a realistic optical fiber probe tip model aided by a deep neural network, 2020, Biomedical Optics Express
  • Deep geometric learning for intracranial aneurysm detection: towards expert rater performance, 2023, Journal of NeuroInterventional Surgery

Frequent co-authors in their research include:

  • Žiga Špiclin
  • Žiga Bizjak
  • Boštjan Likar
  • Lara Dular
  • Peter Naglič

Best Publications

  • A Review of Methods for Correction of Intensity Inhomogeneity in MRI

    U. Vovk;F. Pernus;B. Likar

  • A review of 3D/2D registration methods for image-guided interventions

    Primož Markelj;Dejan Tomaževič;Boštjan Likar;Franjo Pernuš

  • Retrospective correction of MR intensity inhomogeneity by information minimization

    B. Likar;M.A. Viergever;F. Pernus

  • A Survey of Mobile Robots for Distribution Power Line Inspection

    J. Katrasnik;F. Pernus;B. Likar

  • A review of methods for quantitative evaluation of spinal curvature

    Tomaž Vrtovec;Franjo Pernuš;Boštjan Likar

  • A hierarchical approach to elastic registration based on mutual information

    Bostjan Likar;Franjo Pernus

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

    Tim Jerman;Franjo Pernus;Bostjan Likar;Ziga Spiclin

  • 3-D/2-D registration of CT and MR to X-ray images

    D. Tomazevic;B. Likar;T. Slivnik;F. Pernus

  • New Robot for Power Line Inspection

    J. Katrasnik;F. Pernus;B. Likar

  • Retrospective shading correction based on entropy minimization.

    B Likar;J B Maintz;M A Viergever;F Pernus

  • A Framework for Automated Spine and Vertebrae Interpolation-Based Detection and Model-Based Segmentation

    Robert Korez;Bulat Ibragimov;Bostjan Likar;Franjo Pernus

  • Auto-segmentation of organs at risk for head and neck radiotherapy planning: From atlas-based to deep learning methods.

    Tomaž Vrtovec;Domen Močnik;Primož Strojan;Franjo Pernuš

  • A protocol for evaluation of similarity measures for rigid registration

    D. Skerl;B. Likar;F. Pernus

  • Shape Representation for Efficient Landmark-Based Segmentation in 3-D

    Bulat Ibragimov;Bostjan Likar;Franjo Pernus;Tomaz Vrtovec

  • Parametric modelling and segmentation of vertebral bodies in 3D CT and MR spine images.

    Darko Štern;Boštjan Likar;Franjo Pernuš;Tomaž Vrtovec

  • Robust Gradient-Based 3-D/2-D Registration of CT and MR to X-Ray Images

    P. Markelj;D. Tomazevic;F. Pernus;B. Likar

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

    Žiga Lesjak;Alfiia Galimzianova;Aleš Koren;Matej Lukin

  • Comparative evaluation of retrospective shading correction methods

    D Tomazevic;B Likar;F Pernus

  • Model-Based Segmentation of Vertebral Bodies from MR Images with 3D CNNs

    Robert Korez;Boštjan Likar;Franjo Pernuš;Tomaž Vrtovec

  • 3-D/2-D registration by integrating 2-D information in 3-D

    D. Tomazevic;B. Likar;F. Pernus

Frequent Co-Authors

Boštjan Likar
Boštjan Likar University of Ljubljana
Max A. Viergever
Max A. Viergever Utrecht University
Ales Leonardis
Ales Leonardis University of Birmingham
Wolfgang Birkfellner
Wolfgang Birkfellner Medical University of Vienna
Lei Xing
Lei Xing Stanford University
Sebastien Ourselin
Sebastien Ourselin King's College London
Simon K. Warfield
Simon K. Warfield Boston Children's Hospital
Milan Sonka
Milan Sonka University of Iowa
Boudewijn P. F. Lelieveldt
Boudewijn P. F. Lelieveldt Leiden University Medical Center
Frank H. Duffy
Frank H. Duffy Boston Children's Hospital

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online education in Computer Science opens up diverse study and career options beyond traditional degrees. Many students seek flexible and cost-effective learning paths to quickly gain relevant skills. For those aiming to combine business acumen with technical expertise, the most affordable online MBA programs provide a way to advance into management roles without a heavy financial burden.

If you prefer shorter commitments, consider the best one year masters programs online, which can accelerate your journey into specialized tech careers. Likewise, fast degrees online are designed for those eager to enter the workforce quickly in high-demand, well-paying roles.

For individuals interested in the rapidly growing field of artificial intelligence, a range of online AI degree programs offer affordable and accessible ways to gain expertise. By leveraging these flexible online options, you can tailor your educational pathway to fit your career goals and timeline.

Best Scientists Citing Franjo Pernuš

Trending Scientists