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Franjo Pernuš

Showing results (1-10 of 52) with videos related to

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Applied Spectroscopy|November 16, 2010
Deconvolution in acousto-optical tunable filter spectrometryJaka Katrašnik, Franjo Pernuš, Boštjan Likar
Frontiers in Physiology|July 19, 2021
Deep Shape Features for Predicting Future Intracranial Aneurysm GrowthŽiga Bizjak, Franjo Pernuš, Žiga Špiclin
Optics Express|March 14, 2013
A method for characterizing illumination systems for hyperspectral imagingJaka Katrašnik, Franjo Pernuš, Boštjan Likar
Computers in Biology and Medicine|March 26, 2024
Extensive T1-weighted MRI preprocessing improves generalizability of deep brain age prediction modelsLara Dular, Franjo Pernuš, Žiga Špiclin, et al.
Applied Spectroscopy|March 15, 2011
Spectral characterization of near-infrared acousto-optic tunable filter (AOTF) hyperspectral imaging systems using standard calibration materialsMiran Bürmen, Franjo Pernuš, Boštjan Likar
Statistical Methods in Medical Research|February 1, 2018
Reference-free error estimation for multiple measurement methodsHennadii Madan, Franjo Pernuš, Žiga Špiclin
Journal of Biomedical Optics|April 19, 2022
MCDataset: a public reference dataset of Monte Carlo simulated quantities for multilayered and voxelated tissues computed by massively parallel PyXOpto Python packageMiran Bürmen, Franjo Pernuš, Peter Naglič
Biorxiv : the Preprint Server for Biology|May 22, 2023
Extensive T1-weighted MRI Preprocessing Improves Generalizability of Deep Brain Age Prediction ModelsLara Dular, Franjo Pernuš, Žiga Špiclin
Spine|February 4, 2011
Manual and computerized measurement of sagittal vertebral inclination in computed tomography imagesTomaž Vrtovec, Boštjan Likar, Franjo Pernuš
Applied Optics|June 6, 2013
Radiometric calibration and noise estimation of acousto-optic tunable filter hyperspectral imaging systemsJaka Katrašnik, Franjo Pernuš, Boštjan Likar
Pageof 6

Showing results (1-10 of 52) with videos related to

Sort By:
Pageof 6
Applied Spectroscopy|November 16, 2010
Deconvolution in acousto-optical tunable filter spectrometryJaka Katrašnik, Franjo Pernuš, Boštjan Likar
Frontiers in Physiology|July 19, 2021
Deep Shape Features for Predicting Future Intracranial Aneurysm GrowthŽiga Bizjak, Franjo Pernuš, Žiga Špiclin
Optics Express|March 14, 2013
A method for characterizing illumination systems for hyperspectral imagingJaka Katrašnik, Franjo Pernuš, Boštjan Likar
Computers in Biology and Medicine|March 26, 2024
Extensive T1-weighted MRI preprocessing improves generalizability of deep brain age prediction modelsLara Dular, Franjo Pernuš, Žiga Špiclin, et al.
Applied Spectroscopy|March 15, 2011
Spectral characterization of near-infrared acousto-optic tunable filter (AOTF) hyperspectral imaging systems using standard calibration materialsMiran Bürmen, Franjo Pernuš, Boštjan Likar
Statistical Methods in Medical Research|February 1, 2018
Reference-free error estimation for multiple measurement methodsHennadii Madan, Franjo Pernuš, Žiga Špiclin
Journal of Biomedical Optics|April 19, 2022
MCDataset: a public reference dataset of Monte Carlo simulated quantities for multilayered and voxelated tissues computed by massively parallel PyXOpto Python packageMiran Bürmen, Franjo Pernuš, Peter Naglič
Biorxiv : the Preprint Server for Biology|May 22, 2023
Extensive T1-weighted MRI Preprocessing Improves Generalizability of Deep Brain Age Prediction ModelsLara Dular, Franjo Pernuš, Žiga Špiclin
Spine|February 4, 2011
Manual and computerized measurement of sagittal vertebral inclination in computed tomography imagesTomaž Vrtovec, Boštjan Likar, Franjo Pernuš
Applied Optics|June 6, 2013
Radiometric calibration and noise estimation of acousto-optic tunable filter hyperspectral imaging systemsJaka Katrašnik, Franjo Pernuš, Boštjan Likar
Pageof 6