Room ECED-2 : 307
Email sudeep.pv@nitc.ac.in
Office Phone 04952286733
Mobile 09496370647
Areas Of Interest Medical Image Analysis, Machine Learning, Deep Learning

 

Google Scholar Citations (July 2019)

 Citations: 80;      h-index: 5        i10-index: 3

Number of Publications (July 2019)

#National Journals/Conference: 5;      #International Conference: 4        #International Journals: 8

International Journal (2013 - Present):

  1. Sudeep, P.V., Palanisamy, P. and Rajan, J., 2013, December. A hybrid model for Rician noise reduction in MRI. In Advanced Computing, Networking and Security (ADCONS), 2013 2nd International Conference on (pp. 56-61). IEEE.
  2. Sudeep, P.V., Palanisamy, P., Kesavadas, C. and Rajan, J., 2015. Nonlocal linear minimum mean square error methods for denoising MRI. Biomedical Signal Processing and Control20, pp.125-134.
  3. Sudeep, P.V., Niwas, S.I., Palanisamy, P., Rajan, J., Xiaojun, Y., Wang, X., Luo, Y. and Liu, L., 2016. Enhancement and bias removal of optical coherence tomography images: an iterative approach with adaptive bilateral filtering. Computers in biology and medicine71, pp.97-107.
  4. Sudeep, P.V., Palanisamy, P., Rajan, J., Baradaran, H., Saba, L., Gupta, A. and Suri, J.S., 2016. Speckle reduction in medical ultrasound images using an unbiased non-local means method. Biomedical Signal Processing and Control28, pp.1-8.
  5. Sudeep, P.V., Palanisamy, P., Kesavadas, C., Sijbers, J., Arnold, J. and Rajan, J., 2017. A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps. Signal, Image and Video Processing11(5), pp.913-920.
  6. Sudeep, P.V., Palanisamy, P., Kesavadas, C. and Rajan, J., 2018. An improved nonlocal maximum likelihood estimation method for denoising magnetic resonance images with spatially varying noise levels. Pattern Recognition Letters.
  7. Girish, G.N., Anima, V.A., Kothari, A.R., Sudeep, P.V., Roychowdhury, S. and Rajan, J., 2018. A benchmark study of automated intra-retinal cyst segmentation algorithms using optical coherence tomography B-scans. Computer methods and programs in biomedicine153, pp.105-114.
  8. Yamanappa, W., Sudeep, P.V., Sabu, M.K. and Rajan, J., 2018. Non-local means image denoising using Shapiro-Wilk similarity measure. IEEE Access6, pp.66914-66922.

International Conference :

  1. Sudeep, P.V., Navas, K.A. and Sheeba, V.S., 2009, December. Blind Datahiding in Integer Wavelet Transform Domain. In International Conference on Modeling and Simulation (MS09) India (Vol. 1, p. 3).
  2. Sudeep, P.V., Palanisamy, P. and Rajan, J., 2013, December. A hybrid model for Rician noise reduction in MRI. In 2013 2nd International Conference on Advanced Computing, Networking and Security (pp. 56-61). IEEE.
  3. Yamanappa, W, Sudeep, P.V. and Rajan, J., 2019, March. An improved multi-stage multiple image based non-local means image denoising. In International Conference on Machine Learning, Image Processing, Network Security and Data Sciences (MIND 19).
  4. Harshavardhan, G, Sri Venkat, G., Pratyusha, M.G., Kunal Gupta, Volam Priyanka and Sudeep, P.V., 2019, May.  Hardware Implementation of Sign Language to Text Converter using Deep Neural Networks. In International Conference on “Advances in Electronics, Electrical & Computational Intelligence” (ICAEEC 19).

Book Chapter:

  1. Sudeep, P.V., Palanisamy, P. and Rajan, J., 2019. Advances in Ultrasound Despeckling: An Overview. In Advanced Classification Techniques for Healthcare Analysis (pp. 311-335). IGI Global.
  2. Anoop, B.N., Girish, G.N., Sudeep, P.V. and Rajan, J., 2019. Despeckling Algorithms for Optical Coherence Tomography Images: A Review. In Advanced Classification Techniques for Healthcare Analysis (pp. 286-310). IGI Global.

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