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Author

  • Thomas Pock
2017

Variational Photoacoustic Image Reconstruction with Spatially Resolved Projection Data

Hammernik, K., Pock, T. & Nuster, R., 2017, Proc. SPIE. Vol. 10064.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2016

Total variation on a tree

Kolmogorov, V., Pock, T. & Rolinek, M., 3 May 2016, In : SIAM Journal on Imaging Sciences. 9, 2, p. 605-636 32 p.

Research output: Contribution to journalArticleResearchpeer-review

2019

Joint Multi-anatomy Training of a Variational Network for Reconstruction of Accelerated Magnetic Resonance Image Acquisitions

Johnson, P. M., Muckley, M. J., Bruno, M., Kobler, E., Hammernik, K., Pock, T. & Knoll, F., 2019, Machine Learning for Medical Image Reconstruction: Second International Workshop, MLMIR 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings. Knoll, F., Maier, A., Rueckert, D. & Ye, J. (eds.). Cham: Springer, p. 71-79 (Lecture Notes in Computer Science; vol. 11905).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2014

A Deep Variational Model for Image Segmentation

Ranftl, R. & Pock, T., 2014, (Accepted/In press) DAGM Symposium Mustererkennung. .

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

A Comparison of First-order Algorithms for Machine Learning

Yu, W. & Pock, T., 2014, (Accepted/In press) ÖAGM-Meeting. .

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2019

Inverse GANs for accelerated MRI reconstruction

Narnhofer, D., Hammernik, K., Knoll, F. & Pock, T., 2019, Wavelets and Sparsity XVIII.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2017

Automated segmentation and morphometry of muscle fibers from haematoxylin-eosin-stained histological sections

Gerstenberger, C., Karbiener, M., Jaufer, N., Pock, T., Urschler, M. & Gugatschka, M., 19 Oct 2017.

Research output: Contribution to conferenceAbstractResearchpeer-review

L2 or not L2: Impact of Loss Function Design for Deep Learning MRI Reconstruction

Hammernik, K., Knoll, F., Sodickson, D. K. & Pock, T., 2017, Proceedings of the International Society of Magnetic Resonance in Medicine (ISMRM). 0687

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2018

Analysis of the influence of deviations between training and test data in learned image reconstruction

Knoll, F., Hammernik, K., Kobler, E., Pock, T., Sodickson, D. K. & Recht, M. P., 2018.

Research output: Contribution to conferenceAbstractResearchpeer-review

2012

Approximate Envelope Minimization for Curvature Regularity

Heber, S., Ranftl, R. & Pock, T., 2012, Computer Vision -- ECCV 2012. Workshops and Demonstrations: Florence, Italy, October 7-13, 2012, Proceedings, Part III. Springer Berlin - Heidelberg, Vol. 7585. p. 283-292

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2017
2018

Variational Adversarial Networks for Accelerated MR Image Reconstruction

Hammernik, K., Kobler, E., Pock, T., Recht, M. P., Sodickson, D. K. & Knoll, F., 2018, p. 1091.

Research output: Contribution to conferenceAbstractResearchpeer-review

Robust Deformation Estimation in Wood-Composite Materials using Variational Optical Flow

Hofinger, M., Pock, T. & Moosbrugger, T., 5 Feb 2018, p. 97 - 104. 8 p.

Research output: Contribution to conferencePaperResearchpeer-review

Open Access
2014

A higher-order MRF based variational model for multiplicative noise reduction

Chen, Y., Feng, W., Ranftl, R., Qiao, H. & Pock, T., 2014, In : IEEE signal processing letters. 21, 11, p. 1370-1374

Research output: Contribution to journalArticleResearchpeer-review

Open Access
File
2019

Adaptive FISTA for nonconvex optimization

Ochs, P. & Pock, T., 1 Jan 2019, In : SIAM Journal on Optimization. 29, 4, p. 2482-2503 22 p.

Research output: Contribution to journalArticleResearchpeer-review

Convex-Concave Backtracking for Inertial Bregman Proximal Gradient Algorithms in Non-Convex Optimization

Mukkamala, M. C., Ochs, P., Pock, T. & Sabach, S., 2019, In : arXiv.org e-Print archive.

Research output: Contribution to journalArticleResearchpeer-review

2017

Improved Accelerated Model-based Parameter Quantification with Total-Generalized- Variation Regularization.

Maier, O., Schlögl, M., Lesch, A. J., Petrovic, A., Holler, M., Pock, T. & Stollberger, R., 2017, (Accepted/In press).

Research output: Contribution to conferenceAbstractResearchpeer-review

2018

Assessment of the generalization of learned image reconstruction and the potential for transfer learning

Knoll, F., Hammernik, K., Kobler, E., Pock, T., Recht, M. P. & Sodickson, D. K., 2018, In : Magnetic Resonance in Medicine. 81, 1, p. 116-128 13 p.

Research output: Contribution to journalArticleResearchpeer-review

2014

An iteratively reweighted Algorithm for Non-smooth Non-convex Optimization in Computer Vision

Ochs, P., Brox, T., Dosovitskiy, A. & Pock, T., 2014, .

Research output: Book/ReportOther reportResearch

iPiasco: Inertial Proximal Algorithm for strongly convex Optimization

Ochs, P., Brox, T. & Pock, T., 2014, .

Research output: Book/ReportOther reportResearch

iPiano: Inertial Proximal Algorithm for Non-Convex Optimization

Ochs, P., Chen, Y., Brox, T. & Pock, T., 2014, In : SIAM journal on imaging sciences . 7, 2, p. 1388-1419

Research output: Contribution to journalArticleResearchpeer-review

Insights into analysis operator learning: From patch-based sparse models to higher-order MRFs

Chen, Y., Ranftl, R. & Pock, T., 2014, In : IEEE transactions on image processing. 99, 1, p. 1060-1072

Research output: Contribution to journalArticleResearchpeer-review

2019

Joint Reconstruction and Classification of Tumor Cells and Cell Interactions in Melanoma Tissue Sections with Synthesized Training Data

Effland, A., Kobler, E., Brandenburg, A., Klatzer, T., Neuhäuser, L., Hölzel, M., Landsberg, J., Pock, T. & Rumpf, M., 2019, In : International Journal of Computer Assisted Radiology and Surgery.

Research output: Contribution to journalArticleResearchpeer-review

Combining Variational Optimization and Deep Learning for efficient ASL image quality enhancement

Schwarzbach, M., Spann, S. M., Hammernik, K., Aigner, C. S., Pock, T. & Stollberger, R., 2019, Magnetic Resonance Materials in Physics, Biology and Medicine.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

3D Fluid Flow Estimation with Integrated Particle Reconstruction

Lasinger, K., Vogel, C., Pock, T. & Schindler, K., 1 Jan 2019, Pattern Recognition - 40th German Conference, GCPR 2018, Proceedings. Fritz, M., Bruhn, A. & Brox, T. (eds.). Springer-Verlag Italia, p. 315-332 18 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11269 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2016

End-to-End Training of Hybrid CNN-CRF Models for Stereo

Knöbelreiter, P., Reinbacher, C., Shekhovtsov, A. & Pock, T., 30 Nov 2016, In : arXiv.org e-Print archive.

Research output: Contribution to journalArticleResearchpeer-review

File
2015

Continuous Hyper-parameter Learning for Support Vector Machines

Klatzer, T. & Pock, T., 2015, (Accepted/In press) Computer Vision Winter Workshop.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Open Access
File
2011

Global Relabeling for Continuous Optimization in Binary Image Segmentation

Unger, M., Pock, T. & Bischof, H., 2011, (Accepted/In press) Proceedings of EMMCVPR 2011. .

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2015

Vertebrae Segmentation in 3D CT Images based on a Variational Framework

Hammernik, K., Ebner, T., Stern, D., Urschler, M. & Pock, T., 2015, Recent Advances in Computational Methods and Clinical Applications for Spine Imaging and Clinical Applications for Spine Imaging: Part VI. Yao, J., Glocker, B., Klinder, T. & Li, S. (eds.). Switzerland: Springer International Publishing AG , p. 227-233 (Lecture Notes in Computational Vision and Biomechanics; vol. 20).

Research output: Chapter in Book/Report/Conference proceedingChapterResearch

2014

Interactive 2D/3D Image Denoising and Segmentation Tool for Medical Applications

Urschler, M., Leitinger, G. & Pock, T., 2014, Proceedings MICCAI Workshop Interactive Medical Image Computation (IMIC).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Vertebrae Segmentation in 3D CT Images based on a Variational Framework

Hammernik, K., Ebner, T., Stern, D., Urschler, M. & Pock, T., 2014, Proceedings 2nd MICCAI Workshop & Challenge Computational Methods and Clinical Applications in Spine Imaging (CSI). p. 200-207

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2016

Real-Time Intensity-Image Reconstruction for Event Cameras Using Manifold Regularisation

Reinbacher, C., Graber, G. & Pock, T., 23 Sep 2016.

Research output: Contribution to conferencePaperResearchpeer-review

File
2017

Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration

Chen, Y. & Pock, T., 1 Jun 2017, In : IEEE Transactions on Pattern Analysis and Machine Intelligence. 39, 6, p. 1256-1272 17 p., 7527621.

Research output: Contribution to journalArticleResearchpeer-review

2016

Inertial proximal alternating linearized minimization (iPALM) for nonconvex and nonsmooth problems

Pock, T. & Sabach, S., 2016, In : SIAM Journal on Imaging Sciences. 9, 4, p. 1756-1787 32 p.

Research output: Contribution to journalArticleResearchpeer-review

2018

Variational Fusion of Light Field and Photometric Stereo for Precise 3D Sensing within a Multi-Line Scan Framework

Antensteiner, D., Stolc, S. & Pock, T., 2018, Proceedings of the International Conference on Pattern Recognition (ICPR).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2013

Minimizing TGV-Based Variational Models with Non-convex Data Terms

Ranftl, R., Pock, T. & Bischof, H., 2013, 4th International Conference, SSVM 2013, Schloss Seggau, Leibnitz, Austria, June 2-6, 2013.. ., p. 282-293

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2011

Online 3D reconstruciton using Convex Optimization

Graber, G., Pock, T. & Bischof, H., 2011, (Accepted/In press) Proceedings of ICCV 2011. .

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2012

Dense Reconstruction On-the-Fly

Wendel, A., Maurer, M., Graber, G., Pock, T. & Bischof, H., 2012, Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). ., p. 1450-1457

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2015

On learning optimized reaction diffusion processes for effective image restoration

Chen, Y., Yu, W. & Pock, T., 2015, (Accepted/In press) International Conference on Computer Vision. .

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Learning Reaction-Diffusion Models for Image Inpainting

Yu, W., Heber, S. & Pock, T., 2015, (Accepted/In press) Pattern Recognition: 37th German Conference, GCPR 2015, Aachen, Germany, October 7-10, 2015, Proceedings. Springer International Publishing AG , Vol. 9358. p. 356-367

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2017

A Deep Learning Architecture for Limited-Angle Computed Tomography Reconstruction

Hammernik, K., Würfl, T., Pock, T. & Maier, A., 2017, Bildverarbeitung für die Medizin 2017: Informatik aktuell. Springer Verlag Heidelberg

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2019

Determination of the moisture change behavior of cross-laminated timber using an optical flow based computer vision technique

Hofinger, M., Pock, T. & Moosbrugger, T., 2019, In : Wood Material Science and Engineering. 14, 5, p. 332-341

Research output: Contribution to journalArticleResearchpeer-review

2012

Pattern Recognition

Pinz, A. (ed.), Pock, T. (ed.), Bischof, H. (ed.) & Leberl, F. (ed.), 2012, 1 ed. Berlin [u.a.]: Springer. (Lecture Notes in computer science)

Research output: Book/ReportBookResearch

2017

On the Influence of Sampling Pattern Design on Deep Learning-Based MRI Reconstruction

Hammernik, K., Knoll, F., Sodickson, D. K. & Pock, T., 2017, Proceedings of the International Society of Magnetic Resonance in Medicine (ISMRM). 0644

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2019

Crouzeix-Raviart approximation of the total variation on simplicial meshes

Pock, T. & Chambolle, A., 2019.

Research output: Working paperResearchpeer-review

2016

U-shaped Networks for Shape from Light Field

Heber, S., Yu, W. & Pock, T., Sep 2016, British Machine Vision Conference, BMVC 2016.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2017

Variational Networks: Connecting Variational Methods and Deep Learning

Kobler, E., Klatzer, T., Hammernik, K. & Pock, T., 2017, Pattern Recognition: German Conference, GCPR 2017, Proceedings. Springer, p. 281-293 (Lecture Notes in Computer Science; vol. 10496).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2018

A Review of Depth and Normal Fusion Algorithms

Antensteiner, D., Stolc, S. & Pock, T., 2018, In : Sensors .

Research output: Contribution to journalArticleResearchpeer-review

2013

Revisiting loss-specific training of filter-based MRFs for image restoration

Chen, Y., Pock, T., Ranftl, R. & Bischof, H., 2013, 35th German Conference, GCPR 2013, Proceedings. ., p. 271-281

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review