Research Output per year
Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.
- 3 Similar Profiles
Deconvolution
Engineering & Materials Science
Tomography
Engineering & Materials Science
Cameras
Engineering & Materials Science
Image reconstruction
Engineering & Materials Science
Dosimetry
Engineering & Materials Science
Atmospheric turbulence
Engineering & Materials Science
Smartphones
Engineering & Materials Science
Neural networks
Engineering & Materials Science
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 2015 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, (Accepted/In press) In : International Journal of Computer Assisted Radiology and Surgery.Research output: Contribution to journal › Article › Research › peer-review
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 conference › Abstract › Research › peer-review
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. 13 p.Research output: Contribution to journal › Article › Research › peer-review
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 conference › Abstract › Research › peer-review
Variational Deep Learning for Low-Dose Computed Tomography
Kobler, E., Muckley, M., Chen, B., Knoll, F., Hammernik, K., Pock, T., Sodickson, D. & Otazo, R., 10 Sep 2018, 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings. Institute of Electrical and Electronics Engineers, Vol. 2018-April. p. 6687-6691 5 p. 8462312Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Tomography
Dosimetry
X rays
Image quality
Signal to noise ratio
Activities 2018 2018
Variational Deep Learning for low-dose Computed Tomography
Erich Kobler (Speaker)18 Apr 2018
Activity: Talk or presentation › Talk at conference or symposium › Science to science
Deep regularization for medical image analysis
Erich Kobler (Speaker)5 Jun 2018
Activity: Talk or presentation › Invited talk at conference or symposium › Science to science
Learning Convex Regularizers for Image Reconstruction
Erich Kobler (Speaker)21 May 2018 → 25 May 2018
Activity: Talk or presentation › Invited talk at conference or symposium › Science to science
Variational networks: connecting variational methods and deep learning
Erich Kobler (Speaker)19 Mar 2018 → 23 Mar 2018
Activity: Talk or presentation › Invited talk at conference or symposium › Science to science
Learning for Compressed Sensing CT Reconstruction
Erich Kobler (Speaker)7 Jun 2018
Activity: Talk or presentation › Invited talk at conference or symposium › Science to science
Prizes
GCPR 2017 Best Paper Award
Erich Kobler (Recipient), Kerstin Hammernik (Recipient), Thomas Pock (Recipient) & Teresa Klatzer (Recipient), 15 Sep 2017
Prize: Prizes / Medals / Awards
Summa cum Laude Merit Award
Kerstin Hammernik (Recipient), Erich Kobler (Recipient), Thomas Pock (Recipient), Michael P Recht (Recipient), Daniel K Sodickson (Recipient) & Florian Knoll (Recipient), 2018
Prize: Prizes / Medals / Awards