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Personal profile

Biography

Dr Kamlesh Pawar's passion lies in development of novel imaging technologies. His expertise include MR Physics, MR Pulse Sequence Design and MR Image Reconstruction. He has experience in both Academia and Industry. In Industry he has worked on the implementation of Imaging algorithms on embedded processor and development of Instruction set architecture. 
 
Dr Pawar completed his PhD in Electrical and Computer System Engineering on the development of novel imaging methodologies and reconstruction methods for accelerated MR imaging, jointly conferred by IIT Bombay (India) and Monash University (Australia). He also worked on the development of optical embedded waveguide biosensors during his Masters thesis at IIT Bombay.
 
He is currently contributing on the development of accurate quantitative imaging methods and motion correction strategies for MR imaging.   

Keywords

  • Magnetic Resonance Imaging (MRI)
  • MR Pulse Sequence Design
  • MR Data Acquisition and Image Reconstruction Techniques
  • Compressive Sensing MRI
  • Image and Signal Processing
  • Image Processing and Computer Vision

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2012 2018

Chirp Encoded 3D GRE and MPRAGE Sequences

Pawar, K., Chen, Z., Zhang, J., Shah, N. J. & Egan, G. F., Jun 2018.

Research output: Contribution to conferenceAbstractOtherpeer-review

Open Access

Deep learning-based whole head segmentation for simultaneous PET/MR attenuation correction

Baran, J. P., Pawar, K., Ferris, N., Jamadar, S., Cholewa, M., Chen, Z. & Egan, G. F., Jun 2018.

Research output: Contribution to conferenceAbstractOtherpeer-review

Motion Correction in MRI using Deep Convolutional Neural Networks

Pawar, K., Chen, Z., Shah, N. J. & Egan, G. F., Jun 2018.

Research output: Contribution to conferenceAbstractOtherpeer-review

Open Access

ReconNet: A Deep Learning Framework for Transforming MR Image Reconstruction to Pixel Classification

Pawar, K., Chen, Z., Shah, N. J. & Egan, G. F., Jun 2018.

Research output: Contribution to conferenceAbstractOtherpeer-review

Open Access

Residual encoder and convolutional decoder neural network for glioma segmentation

Pawar, K., Chen, Z., Shah, N. J. & Egan, G., 1 Jan 2018, Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 3rd International Workshop, BrainLes 2017, Held in Conjunction with MICCAI 2017, Revised Selected Papers. Switzerland: Springer, p. 263-273 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10670 LNCS).

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