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Roman Jakubicek

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 18, 2020
Deep-learning-based fully automatic spine centerline detection in CT dataRoman Jakubicek, Jiri Chmelik, Petr Ourednicek, et al.
Computer Methods and Programs in Biomedicine|October 11, 2019
Learning-based vertebra localization and labeling in 3D CT data of possibly incomplete and pathological spinesRoman Jakubicek, Jiri Chmelik, Jiri Jan, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 18, 2020
Iterative machine learning based rotational alignment of brain 3D CT dataJiri Chmelik, Roman Jakubicek, Tomas Vicar, et al.
Frontiers in Microbiology|October 3, 2022
Using deep learning for gene detection and classification in raw nanopore signalsMarketa Nykrynova, Roman Jakubicek, Vojtech Barton, et al.
Frontiers in Microbiology|March 6, 2026
Basecalling-free resistance gene identification using a hybrid transformer in raw nanopore signalsRoman Jakubicek, Jevhenij Vorochta, Marketa Jakubickova, et al.
Quantitative Imaging in Medicine and Surgery|April 13, 2026
Automated attenuation analysis of CT pulmonary angiography identifies peripheral hyperperfusion as a prognostic marker in non-surgical chronic thromboembolic pulmonary hypertension (CTEPH)Vojtech Suchanek, Roman Jakubicek, Jan Hrdlicka, et al.
Biomedical Optics Express|November 8, 2021
Self-supervised pretraining for transferable quantitative phase image cell segmentationTomas Vicar, Jiri Chmelik, Roman Jakubicek, et al.
Medical Image Analysis|August 17, 2018
Deep convolutional neural network-based segmentation and classification of difficult to define metastatic spinal lesions in 3D CT dataJiri Chmelik, Roman Jakubicek, Petr Walek, et al.
European Radiology|May 28, 2025
Fully automated Bayesian analysis for quantifying the extent and distribution of pulmonary perfusion changes on CT pulmonary angiography in CTEPHVojtech Suchanek, Roman Jakubicek, Jan Hrdlicka, et al.
Quantitative Imaging in Medicine and Surgery|May 9, 2024
Deep-learning-based reconstruction of T2-weighted magnetic resonance imaging of the prostate accelerated by compressed sensing provides improved image quality at half the acquisition timeMartin Jurka, Iva Macova, Monika Wagnerova, et al.
Pageof 2

Showing results (1-10 of 15) with videos related to

Sort By:
Pageof 2
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 18, 2020
Deep-learning-based fully automatic spine centerline detection in CT dataRoman Jakubicek, Jiri Chmelik, Petr Ourednicek, et al.
Computer Methods and Programs in Biomedicine|October 11, 2019
Learning-based vertebra localization and labeling in 3D CT data of possibly incomplete and pathological spinesRoman Jakubicek, Jiri Chmelik, Jiri Jan, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 18, 2020
Iterative machine learning based rotational alignment of brain 3D CT dataJiri Chmelik, Roman Jakubicek, Tomas Vicar, et al.
Frontiers in Microbiology|October 3, 2022
Using deep learning for gene detection and classification in raw nanopore signalsMarketa Nykrynova, Roman Jakubicek, Vojtech Barton, et al.
Frontiers in Microbiology|March 6, 2026
Basecalling-free resistance gene identification using a hybrid transformer in raw nanopore signalsRoman Jakubicek, Jevhenij Vorochta, Marketa Jakubickova, et al.
Quantitative Imaging in Medicine and Surgery|April 13, 2026
Automated attenuation analysis of CT pulmonary angiography identifies peripheral hyperperfusion as a prognostic marker in non-surgical chronic thromboembolic pulmonary hypertension (CTEPH)Vojtech Suchanek, Roman Jakubicek, Jan Hrdlicka, et al.
Biomedical Optics Express|November 8, 2021
Self-supervised pretraining for transferable quantitative phase image cell segmentationTomas Vicar, Jiri Chmelik, Roman Jakubicek, et al.
Medical Image Analysis|August 17, 2018
Deep convolutional neural network-based segmentation and classification of difficult to define metastatic spinal lesions in 3D CT dataJiri Chmelik, Roman Jakubicek, Petr Walek, et al.
European Radiology|May 28, 2025
Fully automated Bayesian analysis for quantifying the extent and distribution of pulmonary perfusion changes on CT pulmonary angiography in CTEPHVojtech Suchanek, Roman Jakubicek, Jan Hrdlicka, et al.
Quantitative Imaging in Medicine and Surgery|May 9, 2024
Deep-learning-based reconstruction of T2-weighted magnetic resonance imaging of the prostate accelerated by compressed sensing provides improved image quality at half the acquisition timeMartin Jurka, Iva Macova, Monika Wagnerova, et al.
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