Životopis

Curriculum vitae

Informazioni personali

• Nome e cognome: David Svoboda
• Anno di nascita: 1978
• Nazionalità: ceco
• Sesso: maschile
• Madrelingua: ceco
• Lingue straniere: inglese (utente avanzato), italiano (utente base), tedesco (utente base)

Universita/Facolta/Istituto

• Centro di analisi delle imagini biomedici
  Facoltà dell'informatica, Università di Masaryk
  Botanická 68a, 602 00 Brno
  Repubblica Ceca

Funzione, posizione professionale

• Docente

Formazione e qualifiche accademiche

• 2004: Dottorato (PhD) in informatica (Università di Masaryk, Brno, Repubblica Ceca), tesi di dottorato: Cell boundary extraction from 3D histo-pathological images
• 2001: Laurea (Mgr) in informatica (Università di Masaryk, Brno, Repubblica Ceca)
• 1996: Maturità (Liceo matematico, Brno, Repubblica Ceca)

Esperienza professionale

• 2004-: Centro di analisi delle imagini biomedici, Università di Masaryk

Attivita pedagogiche

• 2007-: Insegnante del corso: Filtri digitali
• 2002, 2007-2014: Insegnante del corso: Progetto degli algoritmi I
• 2002-: Insegnante del corso: Manipolazione delle imagini digitali
• 2015-: Insegnante del corso: Introduzione alla manipolazione delle imagini digitali
• 2001: Insegnante del corso: Introduzione alla programmazione

Attivita di ricerca

• Analisi delle imagini biomedici
• Dissimulazione
• Filtri digitali usati nella manipulazione delle imagini
• Ottimazione

Stages professionali

• 2010: Scuola Internazionale di Fisica "Enrico Fermi"; obietto: "Advanced methods in optical fluorescence microscopy towards nanoscopy"; posto: Varenna, Italia
• 2009: 21a Scuola internazionale per i ricercatori di Informatica; obietto: "Molecular and Medical Image Analysis and BioInformatics"; posto: Lipari, Italia
• 2007: Scuola Internazionale ICVSS (International Computer Vision Summer School), posto: Baia Samuele (Ragusa), Sicilia, Italia
• 2005-2006: Universita della citta di Manchester, Inghilterra

Attivita extra-universitarie

• 1998-2011: Composizione tipografico

Bibliografia scelta

• WIESNER, David, Julian SUK, Sven DUMMER, Tereza NEČASOVÁ, Ulman VLADIMÍR, David SVOBODA a Jelmer WOLTERINK. Generative modeling of living cells with SO(3)-equivariant implicit neural representations. Medical Image Analysis. Netherlands: Elsevier, 2024, roč. 2024, č. 91, s. 102991-103008. ISSN 1361-8415. Dostupné z: https://dx.doi.org/10.1016/j.media.2023.102991. URL info
• BURGOS, Ninon a David SVOBODA. Biomedical Image Synthesis and Simulation - Methods and Applications. 1st ed. Elsevier, 2022, 674 s. ISBN 978-0-12-824349-7. URL info
• NEČASOVÁ, Tereza, Ninon BURGOS a David SVOBODA. Validation and evaluation metrics for medical and biomedical image synthesis. In Ninon Burgos, David Svoboda. Biomedical Image Synthesis and Simulation - Methods and Applications. 1st ed. Neuveden: Elsevier, 2022, s. 573-600. The MICCAI Society book Series. ISBN 978-0-12-824349-7. Dostupné z: https://dx.doi.org/10.1016/B978-0-12-824349-7.00032-3. URL info
• ČAPEK, Martin, Michaela BLAŽÍKOVÁ, Ivan NOVOTNÝ, Helena CHMELOVÁ, David SVOBODA, Barbora RADOCHOVÁ, Jiří JANÁČEK a Ondrej HORVÁTH. The Wavelet-Based Denoising Of Images in Fiji, With Example Applications in Structured Illumination Microscopy. Image Analysis & Stereology. International Society for Stereology & Image Analysis, 2021, roč. 40, č. 1, s. 3-16. ISSN 1580-3139. Dostupné z: https://dx.doi.org/10.5566/ias.2432. URL info
• KOZLOVSKÝ, Martin, David WIESNER a David SVOBODA. Transfer Learning in Optical Microscopy. Online. In Svoboda D., Burgos N., Wolterink J., Zhao C. Simulation and Synthesis in Medical Imaging. LNCS 12965. Neuveden: Springer, 2021, s. 77-86. ISBN 978-3-030-87591-6. Dostupné z: https://dx.doi.org/10.1007/978-3-030-87592-3_8. URL info
• SVOBODA, David, Ninon BURGOS, Jelmer M. WOLTERINK a Can ZHAO. Simulation and Synthesis in Medical Imaging. 1. vyd. Cham: Springer, 2021, 154 s. ISBN 978-3-030-87591-6. Dostupné z: https://dx.doi.org/10.1007/978-3-030-87592-3. URL info
• SVOBODA, David a Tereza NEČASOVÁ. Image-based Simulations of Tubular Network Formation. Online. In 17th IEEE International Symposium on Biomedical Imaging. Neuveden: IEEE, 2020, s. 1608-1612. ISBN 978-1-5386-9330-8. Dostupné z: https://dx.doi.org/10.1109/ISBI45749.2020.9098736. URL info
• NEČASOVÁ, Tereza a David SVOBODA. Visual and Quantitative Comparison of Real and Simulated Biomedical Image Data. In Laura Leal-Taixé, Stefan Roth. Computer Vision – ECCV 2018 Workshops. LNCS 11134. Munich, Germany: Springer, 2019, s. 385-394. ISBN 978-3-030-11023-9. Dostupné z: https://dx.doi.org/10.1007/978-3-030-11024-6_28. URL info
• WIESNER, David, David SVOBODA, Martin MAŠKA a Michal KOZUBEK. CytoPacq: A web-interface for simulating multi-dimensional cell imaging. Bioinformatics. Oxford University Press, 2019, roč. 35, č. 21, s. 4531-4533. ISSN 1367-4803. Dostupné z: https://dx.doi.org/10.1093/bioinformatics/btz417. URL info
• WIESNER, David, Tereza NEČASOVÁ a David SVOBODA. On Generative Modeling of Cell Shape Using 3D GANs. Online. In Ricci Elisa, Rota Buló Samuel, Snoek Cees, Lanz Oswald, Messelodi Stefano, Sebe Nicu. Image Analysis and Processing – ICIAP 2019. LNCS 11752. Trento: Springer, 2019, s. 672-682. ISBN 978-3-030-30644-1. Dostupné z: https://dx.doi.org/10.1007/978-3-030-30645-8_61. URL info
• SVOBODA, David, Tereza NEČASOVÁ, Lenka TESAŘOVÁ a Pavel ŠIMARA. Tubular Network Formation Process Using 3D Cellular Potts Model. In Gooya A., Goksel O., Oguz I., Burgos N. Simulation and Synthesis in Medical Imaging. LNCS 11037. Neuveden: Springer, 2018, s. 90-99. ISBN 978-3-030-00535-1. Dostupné z: https://dx.doi.org/10.1007/978-3-030-00536-8_10. URL info
• SVOBODA, David a Vladimír ULMAN. MitoGen: A Framework for Generating 3D Synthetic Time-Lapse Sequences of Cell Populations in Fluorescence Microscopy. IEEE Transactions on Medical Imaging. IEEE Engineering in Medicine and Biology Society, 2017, roč. 36, č. 1, s. 310-321. ISSN 0278-0062. Dostupné z: https://dx.doi.org/10.1109/TMI.2016.2606545. URL info
• SEČKÁŘ, Petr a David SVOBODA. FTutor: An Interactive Guide to the Fundamentals of Frequency Analysis. Computer Applications in Engineering Education. Wiley, 2017, roč. 25, č. 3, s. 508-520. ISSN 1061-3773. Dostupné z: https://dx.doi.org/10.1002/cae.21817. URL info
• SVOBODA, David a Michal KOZUBEK. Multimodal Simulations in Live Cell Imaging. In Tsaftaris S., Gooya A., Frangi A., Prince J. Simulation and Synthesis in Medical Imaging. LNCS 10557. Neuveden: Springer, 2017, s. 89-98. ISBN 978-3-319-68126-9. Dostupné z: https://dx.doi.org/10.1007/978-3-319-68127-6_10. URL info
• SVOBODA, David, Vladimír ULMAN, Peter KOVÁČ, Barbara ŠALINGOVÁ, Lenka TESAŘOVÁ, Irena KRONTORÁD KOUTNÁ a Petr MATULA. Vascular Network Formation in Silico Using the Extended Cellular Potts Model. In 2016 IEEE International Conference on Image Processing. Piscataway, NJ, USA: IEEE Signal Processing Society, 2016, s. 3180-3183. ISBN 978-1-4673-9961-6. Dostupné z: https://dx.doi.org/10.1109/ICIP.2016.7532946. URL info
• ULMAN, Vladimír, David SVOBODA, Matti NYKTER, Michal KOZUBEK a Pekka RUUSUVUORI. Virtual cell imaging: A review on simulation methods employed in image cytometry. Cytometry Part A. John Wiley & Sons, 2016, roč. 89A, č. 12, s. 1057-1072. ISSN 1552-4922. Dostupné z: https://dx.doi.org/10.1002/cyto.a.23031. URL info
• SVOBODA, David, Vladimír ULMAN a Igor PETERLÍK. On Proper Simulation of Chromatin Structure in Static Images As Well As in Time-Lapse Sequences in Fluorescence Microscopy. In Proceedings of 2015 IEEE International Symposium on Biomedical Imaging. Stoughton (WI, USA): Engineering in Medicine and Biology Society, 2015, s. 712-716. ISBN 978-1-4799-2374-8. Dostupné z: https://dx.doi.org/10.1109/ISBI.2015.7163972. info
• SVOBODA, David. Next Step Toward the Automation of Screening for Cervical Cancer. Cytometry Part A. John Wiley & Sons, 2015, roč. 87a, č. 3, s. 195-196. ISSN 1552-4922. Dostupné z: https://dx.doi.org/10.1002/cyto.a.22564. URL info
• ULMAN, Vladimír, Zoltán ORÉMUŠ a David SVOBODA. TRAgen: A Tool for Generation of Synthetic Time-Lapse Image Sequences of Living Cells. In Vittorio Murino, Enrico Puppo, Gianni Vernazza. Proceedings of 18th International Conference on Image Analysis and Processing. Heidelberg, Německo: Springer International Publishing, 2015, s. 623-634. ISBN 978-3-319-23230-0. Dostupné z: https://dx.doi.org/10.1007/978-3-319-23231-7_56. info
• STOKLASA, Roman, Tomáš MAJTNER a David SVOBODA. Efficient k-NN based HEp-2 cells classifier. PATTERN RECOGNITION. OXFORD: PERGAMON-ELSEVIER SCIENCE LTD, 2014, roč. 47, č. 7, s. 2409-2418. ISSN 0031-3203. Dostupné z: https://dx.doi.org/10.1016/j.patcog.2013.09.021. URL info
• WILLIAMS, Ian, Nicholas BOWRING a David SVOBODA. A performance evaluation of statistical tests for edge detection in textured images. Computer Vision and Image Understanding. Elsevier, 2014, roč. 122, May 2014, s. 115-130. ISSN 1077-3142. Dostupné z: https://dx.doi.org/10.1016/j.cviu.2014.02.009. info
• SVOBODA, David, Vladimír ULMAN, Luděk MATYSKA, Martin MAŠKA, Ján BELLA a Stanislav STEJSKAL. On Proper Simulation of Phenomena Influencing Image Formation in Fluorescence Microscopy. In 2014 IEEE International Conference on Image Processing. Neuveden: IEEE Signal Processing Society, 2014, s. 3944-3948. ISBN 978-1-4799-5750-7. Dostupné z: https://dx.doi.org/10.1109/ICIP.2014.7025801. URL info
• SVOBODA, David. The Importance of Computer Generated Data in Fluorescence Microscopy. In Advances in Molecular and Cancer Biology. 2014. info
• SVOBODA, David, Luděk MATYSKA a Vladimír ULMAN. CytoPacq v2.0. 2013. URL info
• SVOBODA, David a Vladimír ULMAN. Towards a Realistic Distribution of Cells in Synthetically Generated 3D Cell Populations. In Alfredo Petrosino. 17th International Conference on Image Analysis and Processing - ICIAP 2013. LNCS 8157, Part II. Berlin, Heidelberg: Springer-Verlag, 2013, s. 429-438. ISBN 978-3-642-41183-0. Dostupné z: https://dx.doi.org/10.1007/978-3-642-41184-7_44. info
• SVOBODA, David a Vladimír ULMAN. Generation of Synthetic Image Datasets for Time-Lapse Fluorescence Microscopy. In Campilho, Aurélio; Kamel, Mohamed. Proceedings of 9th International Conference on Image Analysis and Recognition. LNCS 7325, Part II. Heidelberg: Springer-Verlag, 2012, s. 473-482. ISBN 978-3-642-31297-7. Dostupné z: https://dx.doi.org/10.1007/978-3-642-31298-4_56. info
• MAJTNER, Tomáš a David SVOBODA. Extension of Tamura Texture Features for 3D Fluorescence Microscopy. In 2012 Second Joint 3DIM/3DPVT Conference: 3D Imaging, Modeling, Processing, Visualization & Transmission. Los Alamitos, CA, USA: IEEE Computer Society, 2012, s. 301-307. ISBN 978-0-7695-4873-9. info
• SVOBODA, David, Ondřej HOMOLA a Stanislav STEJSKAL. Generation of 3D Digital Phantoms of Colon Tissue. In M. Kamel and A. Campilho. Proceedings of 8th International Conference on Image Analysis and Recognition. LNCS 6754, Part II. Berlin, Heidelberg: Springer-Verlag, 2011, s. 31-39. ISBN 978-3-642-21595-7. Dostupné z: https://dx.doi.org/10.1007/978-3-642-21596-4_4. info
• SVOBODA, David. Efficient Computation of Convolution of Huge Images. In Giuseppe Maino; Gian Luca Foresti. Image Analysis and Processing - ICIAP 2011. LNCS 6978, Part I. Berlin, Heidelberg: Springer-Verlag, 2011, s. 453-462. ISBN 978-3-642-24084-3. info
• WILLIAMS, Ian, David SVOBODA a Nicholas BOWRING. A Novel Performance Metric For Grey-Scale Edge Detection. In Proceedings of the International Conference on Computer Vision Theory and Applications. Vol. 1. Portugal: Institute for Systems and Technologies of Information, Control and Communication, 2010, s. 91-97. ISBN 978-989-674-028-3. info
• SVOBODA, David, Michal KOZUBEK a Stanislav STEJSKAL. Generation of Digital Phantoms of Cell Nuclei and Simulation of Image Formation in 3D Image Cytometry. Cytometry Part A. John Wiley & Sons, Inc., 2009, roč. 75A, č. 6, s. 494-509. ISSN 1552-4922. Dostupné z: https://dx.doi.org/10.1002/cyto.a.20714. info
• SVOBODA, David, Michal KOZUBEK a Stanislav STEJSKAL. Towards Proper Evaluation of Image Analysis Methods Used in Biomedical Research. In Analytical Cytometry V, International Conference. 2009. ISBN 978-80-254-2561-5. URL info
• SVOBODA, David a Michal KOZUBEK. CytoPacq – On-line Framework for Simulating Fluorescence Microscopy Images. In Hands-on Image Processing, Robotiker-Tecnalia, Bilbao, Spain. 2009. info
• KOZUBEK, Michal, David SVOBODA, Marek KAŠÍK, Martin MAŠKA, Jan HUBENÝ, Stanislav STEJSKAL, Michal SEEMAN a Pavel ZEMČÍK. Simulation of fluorescence image formation in 3D image cytometry. In XXIV International Congress of International Society for Analytical Cytology. 2008. info
• KOZUBEK, Michal, David SVOBODA, Marek KAŠÍK, Martin MAŠKA, Jan HUBENÝ, Stanislav STEJSKAL, Michal SEEMAN a Pavel ZEMČÍK. Simulation of fluorescence image formation in 3D light microscopy. In 8th Meeting of European Light Microscopy Initiative. 2008. info
• WILLIAMS, Ian, David SVOBODA, Nicholas BOWRING a Elizabeth GUEST. Statistical Edge Detection of Concealed Weapons Using Artificial Neural Networks. In Proceedings of SPIE-IS&T Electronic Imaging. Vol. 6812. Bellingham, Washington: SPIE, 2008, s. 68121J-1-12, 12 s. ISBN 978-0-8194-6984-7. URL info
• SVOBODA, David, Marek KAŠÍK, Martin MAŠKA, Jan HUBENÝ, Stanislav STEJSKAL a Michal ZIMMERMANN. On Simulating 3D Fluorescent Microscope Images. In Computer Analysis of Images and Patterns. Berlin, Heidelberg: Springer-Verlag, 2007, s. 309-316. ISBN 978-3-540-74271-5. URL info
• MAŠKA, Martin, Jan HUBENÝ, David SVOBODA a Michal KOZUBEK. A Comparison of Fast Level Set-Like Algorithms for Image Segmentation in Fluorescence Microscopy. Online. In 3rd International Symposium on Visual Computing. Berlin, Heidelberg: Spinger-Verlag, 2007, s. 571-581. ISBN 978-3-540-76855-5. URL info
• SVOBODA, David, Ian WILLIAMS, Nicholas BOWRING a Elizabeth GUEST. Statistical techniques for edge detection in histological images. In First International Conference on Computer Vision Theory and Applications. Portugalsko: INSTICC Press, 2006, s. 457-462. ISBN 972-8865-40-6. info
• WILLIAMS, Ian, David SVOBODA, Nicholas BOWRING a Elizabeth GUEST. Improved statistical edge detection through neural networks. In 10th Conference on Medical Image Understanding and Analysis. Manchester: BMVA, 2006, s. 56-60. ISBN 1-901727-31-9. URL info
• KOZUBEK, Michal, Pavel MATULA, Petr MATULA a David SVOBODA. Analysis of biomedical image data acquired using optical microscopy. In Prague Post Genome Technology Workshop. Prague, Czech Republic: Czech Pattern Recognition Society, 2005, s. 24-27. ISBN 80-01-03239-6. info
• SVOBODA, David. Towards a Fully Automated Tissue Cell Segmentation Method. In Visualization, Imaging, and Image Processing. Anaheim, Calgary, Zurich: ACTA Press, 2004, s. 430-434. ISBN 0-88986-454-3. URL info
• SVOBODA, David a Pavel MATULA. Multilevel Adaptive Thresholding and Dual Simplex Mesh Deformation as a Tool for Tissue Reconstruction. In Visualization, Imaging, and Image Processing. Anaheim, Calgary, Zurich: ACTA Press, 2003, s. 499-503. ISBN 0-88986-382-2. URL info
• MATULA, Pavel a David SVOBODA. 3D Object reconstructions in image cytometry. In Biophysics of the Genome. Brno: Masaryk University, 2003, s. 49-50. ISBN 80-210-3226-X. info
• SVOBODA, David a Pavel MATULA. Tissue image reconstruction: Localization of nuclei markers and segmentation based on deformable models. In Biophysics of the Genome. Brno: Masaryk University, 2003, s. 67-70. ISBN 80-210-3226-X. info
• SVOBODA, David a Pavel MATULA. Tissue Reconstruction Based on Deformation of Dual Simplex Meshes. In Discrete Geometry for Computer Imagery. Berlin, Heidelberg, New York: Springer, 2003, s. 514-523. ISBN 3-540-20499-7. URL info
• MATULA, Pavel a David SVOBODA. Spherical Object Reconstruction Using Simplex Meshes from Sparse Data. In Discrete Geometry for Computer Imagery. Berlin Heidelberg New York: Springer-Verlag, 2003, s. 524-533. ISBN 3-540-20499-7. URL info
• MATULA, Pavel a David SVOBODA. Cell Nuclei Segmentation Using Star-Shaped Simplex Meshes. In Biophysics of the Genome and Its Interactions. Brno: Masaryk University, 2002, s. 74-76. ISBN 80-210-2853-X. info
• MATULA, Pavel a David SVOBODA. Spherical Object Reconstruction Using Star-Shaped Simplex Meshes. In Energy Minimization Methods in Computer Vision and Pattern Recognition. Berlin, Heidelberg, New York: Springer-Verlag, 2001, s. 608-620. ISBN 3-540-42523-3. URL info

1. 2. 2018

Další varianty: angličtina(1), čeština(1)