Pattern Recognition and
Image Processing Group
Institute of Visual Computing and Human-Centered Technology
- Image processing (2D / 3D / nD)
- Medical image analysis
- Pattern recognition & machine learning
Scientific activities and memberships
Reviewer for mayor journals and conferences related to medical imagages including Medical Image Analysis, MICCAI, IEEE TVCG, and Eurographics. Co-editor of the Central European Seminar on Computer Graphics. Member of Austrian Association for Pattern Recognition (OAGM). Former member of Eurographics, IEEE Computer Society, and MICCAI Society.
- 2020 ACVRW WIE Best Paper Award
- 2008 Winner of MICCAI Grand Challenge: 3D Segmentation in Clinic
- 2002 IEEE Visualization Best Case Study
- 2002 PhD in computer science, Vienna University of Technology
- 1996 MSc in mathematics, Comenius University, Bratislava
- 2018 – assistant professor, Vienna University of Technology, Austria
- 2003 – 2018 senior researcher and project lead, VRVis, Vienna, Austria
- 1998 – 2002 research assistant, Vienna University of Technology, Austria
- 1998 – 1998 university assistant, Comenius University, Bratislava, Slovakia
- 1996 – 1998 software developer, TatraMed / Howmedica Leibinger, Freiburg, Germany
- 2020 – Water’s Gateway to Heaven
- 2017 – 2018 Automated recognition and measurement of thyroid lobes in ultrasound
- 2014 – 2016 Osteon: Visual Computing Techniques for Automated Detection of Osteoporosis and Osteoarthritis
Selection from about 80 publications
D. Major, J. Hladůvka, and K. Bühler. Method, apparatus and system for automated spine labeling. WO/2014/016268A1; EP 2690596B1; US 9408584B2. 2014.
J. Hladůvka, D. Major, and K. Bühler. Method, apparatus and system for identifying a specific part of a spine in an image. WO/2014/114588A1; EP 2948062A1; US 9763635B2. 2014.
J. Hladůvka, D. Major, and K. Bühler. Method, apparatus and system for localizing a spine. WO/2013/135812A1; EP 2639763B1; US 9406122B2. 2013.
S. Bruckner, V. Šoltészová, K. Bühler, and J. Hladůvka. Visual queries in data exploration. WO/2011/038427A1; EP 2483804B1. 2011.
J. Hladůvka. Derivatives and eigensystems for volume-data analysis and visualization, PhD thesis, Institute of Computer Graphics; Algorithms, Vienna University of Technology, 2001.
J. Hladůvka. Algorithms of fast volume rendering, Master’s thesis, Department of Computer Graphics; Image Processing, Comenius University Bratislava, 1996.
L. Jakaite, V. Schetinin, J. Hladůvka, S. Minaev, A. Ambia, and W. Krzanowski. Deep learning for early detection of pathological changes in X-ray bone microstructures: Case of osteoarthritis, Scientific Reports, vol. 11, no. 2294, 2021.
A. A. Novikov, D. Major, D. Lenis, J. Hladůvka, M. Wimmer, and K. Bühler. Fully convolutional architectures for multi-class segmentation in chest radiographs, IEEE Transactions on Medical Imaging, vol. 37, no. 8, pp. 1865–1876, 2018.
D. Major, J. Hladůvka, F. Schulze, and K. Bühler. Automated landmarking and labeling of fully and partially scanned spinal columns in CT images, In Medical Image Analysis, vol. 17, no. 8, pp. 1151–1163, 2013.
S. Bruckner, V. Šoltészová, E. Gröller, J. Hladůvka, K. Bühler, J. Y. Yu, and B. J. Dickson. BrainGazer – visual queries for neurobiology research, IEEE Transactions on Visualization and Computer Graphics, vol. 15, no. 6, pp. 1497–1504, 2009.
J. Hladůvka and E. Gröller. Exploiting the Hessian matrix for content-based retrieval of volume-data features, The Visual Computer, vol. 18, no. 4, pp. 207–217, 2002.
J. Hladůvka and E. Gröller. Smallest 2nd-order derivatives for efficient volume-data representation, Computers and Graphics, vol. 26, no. 2, pp. 229–238, 2002.
Conferences and Workshops
V. Renner and J. Hladůvka. Towards identification of incorrectly segmented OCT scans, in Joint austrian computer vision and robotics workshop, 2020, pp. 159–165.
D. Batavia, J. Hladůvka, and W. Kropatsch. Partitioning 2D images into prototypes of slope region, in Computer analysis of images and patterns, 2019, pp. 363–374.
V. V. Kniaz, V. A. Knyaz, J. Hladůvka, W. G. Kropatsch, and V. A. Mizginov. ThermalGAN: Multimodal Color-to-Thermal Image Translation for Person Re-Identification in Multispectral Dataset, in Computer Vision – ECCV 2018 Workshops, 2019, pp. 606–624.
J. Hladůvka, A. Enkhbayar, B. Norman, and R. Ljuhar. Automated ROI placement and trabecula-driven orientation for radiographic texture analyses of calcaneus, in Proceedings of international symposium on biomedical imaging, 2016, pp. 164–167.
J. Hladůvka, D. Major, and K. Bühler. Bone profiles: Simple, fast, and reliable spine localization in CT scans, in Recent advances in computational methods and clinical applications for spine imaging (lecture notes in computational vision and biomechanics), 2015, vol. 20, pp. 173–184.
S. Zambal, K. Bühler, and J. Hladůvka. Entropy-optimized texture models, in Proceedings of medical image computing and computer–assisted intervention, 2008, pp. 213–221.
S. Zambal, J. Hladůvka, and K. Bühler. Improving segmentation of the left ventricle using a two-component statistical model, in Proceedings of medical image computing and computer–assisted intervention, 2006, pp. 151–158.
J. Hladůvka and K. Bühler. MDL spline models: Gradients and polynomial reparameterisations, in Proceedings of british machine vision conference, 2005, vol. 2, pp. 869–878.
A. Kanitsar, T. Theußl, L. Mroz, M. Šrámek, A. V. i Bartolı́, B. Csébfalvi, J. Hladůvka, D. Fleischmann, M. Knapp, R. Wegenkittl, P. Felkel, S. Röttger, S. Guthe, W. Purgathofer, and E. Gröller. Christmas tree case study: Computed tomography as a tool for mastering complex real world objects with applications in computer graphics., in Proceedings of IEEE visualization, 2002, pp. 489–492.
T. Theußl, T. Möller, J. Hladůvka, and E. Gröller. Reconstruction issues in volume visualization, in Data visualization: The state of the art, 2003, pp. 109–126.
J. Hladůvka and E. Gröller. Direction-driven shape-based interpolation of volume data, in Proceedings of vision, modeling, and visualization, 2001, pp. 113–120, 521.
J. Hladůvka, A. König, and E. Gröller. Salient representation of volume data, in Data visualization 2001, proceedings of the Joint Eurographics – IEEE TCVG symposium on visualization, 2001, pp. 203–211, 351.