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Krishna Kumar Perikamana
Krishna Kumar Perikamana
External Consultant, Academics and Research, Indian Institute for Human Settlements
Verified email at iihs.ac.in
Title
Cited by
Cited by
Year
A review on carotid ultrasound atherosclerotic tissue characterization and stroke risk stratification in machine learning framework
AM Sharma, A Gupta, PK Kumar, J Rajan, L Saba, I Nobutaka, JR Laird, ...
Current atherosclerosis reports 17 (9), 1-13, 2015
582015
State-of-the-art review on automated lumen and adventitial border delineation and its measurements in carotid ultrasound
PK Kumar, T Araki, J Rajan, JR Laird, A Nicolaides, JS Suri
Computer methods and programs in biomedicine 163, 155-168, 2018
282018
Accurate lumen diameter measurement in curved vessels in carotid ultrasound: an iterative scale-space and spatial transformation approach
P Krishna Kumar, T Araki, J Rajan, L Saba, F Lavra, N Ikeda, AM Sharma, ...
Medical & biological engineering & computing 55 (8), 1415-1434, 2017
282017
Carotid inter‐adventitial diameter is more strongly related to plaque score than lumen diameter: An automated tool for stroke analysis
L Saba, T Araki, P Krishna Kumar, J Rajan, F Lavra, N Ikeda, AM Sharma, ...
Journal of Clinical Ultrasound 44 (4), 210-220, 2016
282016
Segmentation of intima media complex from carotid ultrasound images using wind driven optimization technique
Y Nagaraj, P Madipalli, J Rajan, PK Kumar, AV Narasimhadhan
Biomedical Signal Processing and Control 40, 462-472, 2018
252018
Two automated techniques for carotid lumen diameter measurement: regional versus boundary approaches
T Araki, PK Kumar, HS Suri, N Ikeda, A Gupta, L Saba, J Rajan, F Lavra, ...
Journal of medical systems 40 (7), 1-19, 2016
242016
A hybrid method for object identification and event detection in video
KK Perikamana, L Parameswaran
Computer Vision, Pattern Recognition, Image Processing and Graphics …, 2013
17*2013
Ultrasound-based automated carotid lumen diameter/stenosis measurement and its validation system
T Araki, AM Kumar, P Krishna Kumar, A Gupta, L Saba, J Rajan, F Lavra, ...
Journal for Vascular Ultrasound 40 (3), 120-134, 2016
122016
Magnetic resonance image denoising using nonlocal maximum likelihood paradigm in DCT‐framework
PK Kumar, P Darshan, S Kumar, R Ravindra, J Rajan, L Saba, JS Suri
International Journal of Imaging Systems and Technology 25 (3), 256-264, 2015
92015
Coupled PDE for ultrasound despeckling using ENI classification
R Soorajkumar, P Krishnakumar, D Girish, J Rajan
Procedia Computer Science 89, 658-665, 2016
42016
Fourth order PDE based ultrasound despeckling using ENI classification
R Soorajkumar, PK Kumar, D Girish, J Rajan
2016 International Conference on Signal Processing and Communications (SPCOM …, 2016
32016
A CNN based method for Sub-pixel Urban Land Cover Classification using Landsat-5 TM and Resourcesat-1 LISS-IV Imagery
KK Perikamana, K Balakrishnan, P Tripathy
arXiv preprint arXiv:2112.08841, 2021
12021
A semi-automatic method for carotid artery wall segmentation in MR images
PK Kumar, C Kesavadas, J Rajan
2016 IEEE Annual India Conference (INDICON), 1-6, 2016
12016
Deep learning approach for monitoring urban land cover changes
KK Perikamana, K Balakrishnan, P Tripathy
Earth Observation in Urban Monitoring, 171-196, 2024
2024
Accurate Measurement of Carotid Lumen Diameter and Narrowing Utilizing Ultrasound
AM Sharma, T Araki, K Kumar, N Ikeda, F Lavra, J Rajan, L Saba, ...
Arteriosclerosis, Thrombosis, and Vascular Biology 35 (suppl_1), A509-A509, 2015
2015
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