Mayank Patwari
Mayank Patwari, M. Sc.
Academic CV
- 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
Publications
2023
Journal Articles
Reducing the risk of hallucinations with interpretable deep learning models for low-dose CT denoising: comparative performance analysis
In: Physics in Medicine and Biology 68 (2023)
ISSN: 0031-9155
DOI: 10.1088/1361-6560/acfc11
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2022
Journal Articles
Trainable joint bilateral filters for enhanced prediction stability in low-dose CT
In: Scientific Reports 12 (2022), Article No.: 17540
ISSN: 2045-2322
DOI: 10.1038/s41598-022-22530-4
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Ultra low‐parameter denoising: Trainable bilateral filter layers in computed tomography
In: Medical Physics 49 (2022), p. 5107-5120
ISSN: 0094-2405
DOI: 10.1002/mp.15718
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Limited parameter denoising for low-dose X-ray computed tomography using deep reinforcement learning
In: Medical Physics 49 (2022), p. 4540 - 4553
ISSN: 0094-2405
DOI: 10.1002/mp.15643
URL: https://aapm.onlinelibrary.wiley.com/doi/10.1002/mp.15643
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A quantitative comparison of plantar soft tissue strainability distribution and homogeneity between ulcerated and non-ulcerated patients using ultrasound strain elastography
In: Proceedings of the Institution of Mechanical Engineers Part H-Journal of Engineering in Medicine (2022)
ISSN: 0954-4119
DOI: 10.1177/09544119221074786
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2021
Conference Contributions
JBFnet: Low Dose CT-denoising by Trainable Joint Bilateral Filtering
German Workshop on Medical Image Computing, 2021 (Regensburg, March 7, 2021 - March 9, 2021)
In: Christoph Palm, Heinz Handels, Klaus Maier-Hein, Thomas M. Deserno, Andreas Maier, Thomas Tolxdorff (ed.): Informatik aktuell 2021
DOI: 10.1007/978-3-658-33198-6_76
URL: https://link.springer.com/chapter/10.1007/978-3-658-33198-6_76
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Deep Learning based Model Observers for Multi - Modal Imaging
16th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Leuven, Belgium, July 19, 2021 - July 23, 2021)
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2020
Conference Contributions
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
URL: https://link.springer.com/chapter/10.1007/978-3-030-59713-9_49
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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
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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
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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
DOI: 10.1007/978-3-030-33843-5_11
URL: https://link.springer.com/chapter/10.1007/978-3-030-33843-5_11
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Student Projects
Title | Type | Status | Student |
---|---|---|---|
Low Dose Helical CBCT denoising by domain filtering with deep reinforcement learning improved by Neural Ordinary Differential Equations approach | MA thesis | finished | Wooram Kang |
Helical CT Reconstruction with Bilateral Sinogram/Volume Domain Denoisers | Project | finished | Wooram Kang |
Investigating augmented filtering approaches towards noise removal in low dose CT | MA thesis | finished | Zhenju Yin |
Deep Learning based Model Observers for Multi-modal Imaging | Project | finished | Hamidreza Naderi Boldaji |