Mayank Patwari, M. Sc.
Researcher
Martensstr. 3
91058 Erlangen
Department of Computer Science
Chair of Computer Science 5 (Pattern Recognition)
Martensstr. 3
91058 Erlangen
- Phone number: +49 9131 85 27894
- Fax number: +49 9131 85 27270
- Email: mayank.patwari@siemens-healthineers.com
- Website: https://lme.tf.fau.de/person/patwari/
- Since 11/2019:
Researcher at Pattern Recognition Lab - Since 10/2018:
Researcher at Siemens Healthineers - 04/2018 – 09/2018:
Master Thesis at the Mobile Health Systems Lab, ETH Zurich - 10/2016 – 09/2018:
M.Sc. Biomedical Computing, TU Munich - 09/2012 – 12/2015:
B.Eng. Medical Engineering, University of Hong Kong
No projects found.
2020
Conference Contributions
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JBFnet - Low Dose CT Denoising by Trainable Joint Bilateral Filtering
23rd International Conference on Medical Image Computing and Computer Assisted Surgery (MICCAI) (Lima, Peru, October 5, 2020 - October 7, 2020)
In: Martel, A.L., Abolmaesumi, P., Stoyanov, D., Mateus, D., Zuluaga, M.A., Zhou, S.K., Racoceanu, D., Joskowicz, L. (ed.): Proceedings of the 23rd International Conference on Medical Image Computing and Computer Assisted Surgery (MICCAI) 2020
DOI: 10.1007/978-3-030-59713-9_49
BibTeX: Download - , , , :
Low Dose CT Denoising via Joint Bilateral Filtering and Intelligent Parameter Optimization
6th International Conference on Image Formation in X-Ray Computed Tomography (Regensburg, August 3, 2020 - August 7, 2020)
In: Proceeding of the 6th International Conference on Image Formation in X-Ray Computed Tomography 2020
URL: https://www.ct-meeting.org/data/ProceedingsCTMeeting2020.pdf
BibTeX: Download - , , , :
Low dose CT denoising with residual convolutional networks and deep learned perceptual loss
European Congress of Radiology (Vienna, Austria, July 15, 2020 - July 19, 2020)
DOI: 10.26044/ecr2020/C-03463
URL: https://epos.myesr.org/poster/esr/ecr2020/C-03463
BibTeX: Download
2019
Conference Contributions
- , , , :
Measuring CT Reconstruction Quality with Deep Convolutional Networks
Second International Workshop on Machine Learning for Medical Image Reconstruction (Shenzhen, China, October 17, 2019 - October 17, 2019)
In: Knoll F., Maier A., Rueckert D., Ye J. (ed.): Machine Learning for Medical Image Reconstruction 2019
URL: https://link.springer.com/chapter/10.1007/978-3-030-33843-5_11
BibTeX: Download
| Title | Type | Status | Student |
|---|---|---|---|
| Helical CT Reconstruction with Bilateral Sinogram/Volume Domain Denoisers | Project | running | Wooram Kang |
| Noise Removal Models for Ultra-Low Parameter Denoising Approaches in Clinical CT | MA thesis | running | Zhenju Yin |
| Deep Learning based Model Observers for Multi-modal Imaging | Project | finished | Hamidreza Naderi Boldaji |
| Disentanglement Learning for Processing Medical Images | MA thesis | running | Akshat Shrivastava |