Hi, I am Raji. I am a faculty member (Assistant Professor) in the School of Data Science at the Indian Institute of Science Education and Research (IISER), Thiruvananthapuram. Before this, I was a Post-doctoral Fellow in the Medical Imaging Group, headed by Prof. Phaneendra K. Yalavarthy in the Department of Computational and Data Sciences, Indian Institute of Science Bangalore. From 2021 to 2023, I was a C. V. Raman Post-doctoral Fellow in the same Group. I completed Ph.D. in the area of MR image reconstruction from Indian Institute of Information Technology and Management- Kerala under the guidance of Prof. Joseph Suresh Paul. My Ph.D. work was focused on the proper use of regularized solution that facilitates noise reduction and artifact suppression in the reconstructed magnetic resonance image. Prior to Ph.D., I received bachelor’s degree in Electronics and Communication Engineering from the Mahatma Gandhi university, Kottayam and master's degree in Signal Processing from the Cochin university of science and technology, Kochi in 2011 and 2013. My research interests include application of regularization for image reconstruction techniques, compressed sensing and deep learning. I am also interested in inverse problems and computational methods for medical imaging.
I am looking for bright students to join my lab. See projects and publications to learn about our research work. We also continuously seek new research interns at final year undergraduate and graduate levels. Interested folks are welcome to contact me through email with your CV and statement of purpose.
Publications
Journals
Karan R. Gujarati, Lokesh Bathala, Vaddadi Venkatesh, Raji Susan Mathew, and Phaneendra K. Yalavarthy, "Transformer-based Automated Segmentation of the Median Nerve in Ultrasound Videos of Wrist-to-Elbow Region ," IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 2023 (In press). (doi: 10.1109/TUFFC.2023.3330539).
Raji Susan Mathew, Naveen Paluru and Phaneendra K. Yalavarthy, "Model-Resolution based Deconvolution for Improved Quantitative Susceptibility Mapping," NMR in Biomedicine, 2023 (In press). (doi: https://doi.org/10.1002/nbm.5055 ).
Raji Susan Mathew and Joseph Suresh Paul, “Automated regularization parameter selection using continuation based proximal method for compressed sensing MRI”, IEEE Transactions on Computational Imaging. 6, 1309-1319, Aug. 2020. (doi: 10.1109/TCI.2020.3019111)
Raji Susan Mathew and Joseph Suresh Paul, “Sparsity Promoting Adaptive Regularization for Compressed Sensing Parallel MRI", IEEE Transactions on Computational Imaging. 4(1), 147-59, Mar. 2018. (doi: 10.1109/TCI.2017.2787911)
Raji Susan Mathew and Joseph Suresh Paul, “A Frequency-Dependent Regularization for Autocalibrating Parallel MRI Using the Generalized Discrepancy Principle,” IEEE Transactions on Computational Imaging. 3(4), 891-900, Dec. 2017. (doi: 10.1109/TCI.2017.2707979)
Raji Susan Mathew and Joseph Suresh Paul, “Improving image quality in low snr parallel acquisition using a weighted least squares GRAPPA reconstruction,” Imaging in Medicine. 8(2), 16-22, 2016.
Conference Publications
Raji Susan Mathew and Joseph Suresh Paul, “A Quantitative Comparison of the Role of Parameter Selection for Regularization in GRAPPA-Based Autocalibrating Parallel MRI,” In Proceedings of 3rd International Conference on Computer Vision and Image Processing 2020 (pp. 35-45). Springer, Singapore.
Raji Susan Mathew and Joseph Suresh Paul, “Combination of global and nonlocal sparse regularization priors for MR image reconstruction”, In TENCON 2019- 2019 IEEE Region 10 Conference (TENCON) 2019 Oct 17 (pp. 2680-2684). IEEE.
Raji Susan Mathew and Joseph Suresh Paul, “Adaptive Fast Composite Splitting Algorithm for MR Image Reconstruction,” In International Conference on Machine Intelligence and Signal Processing 2019 Sep 7 (pp. 161-171). Springer, Singapore.
Book
Joseph Suresh Paul and Raji Susan Mathew, Regularized Image Reconstruction in Parallel MRI with MATLAB, CRC press, Taylor & Francis Group, LLC. October 2019.
Book Chapter
Raji Susan Mathew*, Naveen Paluru*, and Phaneendra K. Yalavarthy, Artificial Intelligence in Healthcare - India Case Study, Biotechnology in India - Reworking a Strategy, Springer Nature, (2023). [* Equal Contribution] (Under Revision)
Joseph Suresh Paul, Raji Susan Mathew and M. S. Renjith, Theory of Parallel MRI and Cartesian SENSE Reconstruction: Highlight. In Medical Imaging in Clinical Applications, (pp. 311-328). Springer International Publishing, 2016.
Thesis
Raji Susan Mathew, Adaptive Regularization Techniques for Image Reconstruction in Accelerated MRI, Ph.D Thesis, Cochin University of Science and Technology, Feb. 2021.
Symposium/Workshops/Posters/Challenge Participation
Raji Susan Mathew, Naveen Paluru and Phaneendra K. Yalavarthy, "Model-Resolution based Deconvolution for Improved Quantitative Susceptibility Mapping," Poster Presentation, Medical Image Computing Workshop, Organized by IISc Bangalore, 24-25 Feb, (2023). [Certificate].
Naveen Paluru, Raji Susan Mathew, and Phaneendra K. Yalavarthy, "TTC-QSM : Model Based Test Time Correction for Improved Quantitative Susceptibility Mapping", Poster Presentation, Medical Image Computing Workshop, Organized by IISc Bangalore, 24-25 Feb, (2023).
Vaddadi Venkatesh, Raji Susan Mathew, and Phaneendra K. Yalavarthy, "SpiNet-QSM: Model-based Deep Learning with Schatten p‐norm regularization for Quantitative Susceptibility Mapping", Poster Presentation, Medical Image Computing Workshop, Organized by IISc Bangalore, 24-25 Feb, (2023).
Ashish Verma, Raji Susan Mathew, Phaneendra K. Yalavarthy," A Deep Learning based Back Project Filter Method for Limited Angle Computed Tomography", HTC Tomographic Challenge (2022). [Github].[Certificate].
Invited Talks
"Data-driven Approaches for Improved Reconstruction and Segmentation in Medical Imaging" at IEEE SPS SBC, IIT Kharagpur (11/10/2023).
"Development of Artificial Intelligence Solutions for Medical Image Analysis" at AI in Neurology Workshop (KNACON 2023) at Shivamogga (28/04/2023).
"Compressed Sensing MRI: k-space Sampling to Reconstruction" at Samvaad: [Medical AI], IIIT Bangalore (14/03/2022).