Mayank Patwari

2022

Journal Articles

• Wagner F., Thies M., Denzinger F., Gu M., Patwari M., Ploner S., Maul N., Pfaff L., Huang Y., Maier A.:
  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
  BibTeX: Download
• Wagner F., Thies M., Gu M., Huang Y., Pechmann S., Patwari M., Ploner S., Aust O., Uderhardt S., Schett G., Christiansen SH., Maier A.:
  Ultra low‐parameter denoising: Trainable bilateral filter layers in computed tomography
  In: Medical Physics (2022)
  ISSN: 0094-2405
  DOI: 10.1002/mp.15718
  BibTeX: Download
• Patwari M., Gutjahr R., Raupach R., Maier A.:
  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
  BibTeX: Download
• Patwari M., Chatzistergos P., Sundar L., Chockalingam N., Ramachandran A., Naemi R.:
  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
  BibTeX: Download

2021

Conference Contributions

• Patwari M., Gutjahr R., Raupach R., Maier A.:
  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
  BibTeX: Download
• Naderi Boldaji H., Patwari M., Reymann M., Gutjahr R., Raupach R., Maier A.:
  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)
  BibTeX: Download

2020

Conference Contributions

• Patwari M., Gutjahr R., Raupach R., Maier A.:
  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
  BibTeX: Download
• Patwari M., Gutjahr R., Raupach R., Maier A.:
  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
• Patwari M., Gutjahr R., Raupach R., Maier A.:
  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

• Patwari M., Gutjahr R., Raupach R., Maier A.:
  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
  BibTeX: Download