Chandrasekharan Kesavadas

23 papers B 2Journal 17Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
A dual encoder-decoder multi-task 3D deep learning framework for the segmentation of focal cortical dysplasia lesions.
Biomed. Signal Process. Control.
S. Niyas, Chandrasekharan Kesavadas, Jeny Rajan
2023 J jnl
Resting-State Functional Connectivity in Relapsing-Remitting Multiple Sclerosis with Mild Disability: A Data-Driven, Whole-Brain Multivoxel Pattern Analysis Study.
Brain Connect.
Gowthami Nair, Sruthi S. Nair, Karumattu Manattu Arun, Paúl Camacho, Elshal Bava, Priya Ajayaghosh, Ramshekhar N. Menon, Muralidharan Nair, Chandrasekharan Kesavadas, Sheeba Arnold Anteraper
2023 J jnl
Unsupervised Multi-Latent Space RL Framework for Video Summarization in Ultrasound Imaging.
IEEE J. Biomed. Health Informatics
Roshan P. Mathews, Mahesh Raveendranatha Panicker, Abhilash Rakkunedeth Hareendranathan, Yale Tung Chen, Jacob L. Jaremko, Brian Buchanan, Kiran Vishnu Narayan, Chandrasekharan Kesavadas, Greeta Mathews
2022 J jnl
An Improved Deep Persistent Memory Network for Rician Noise Reduction in MR Images.
Biomed. Signal Process. Control.
Anate Mary Augustin, Chandrasekharan Kesavadas, P. V. Sudeep
2022 J jnl
Deep-ASL enhancement technique in arterial spin labeling MRI - A novel approach for the error reduction of partial volume correction technique with linear regression algorithm.
J. Comput. Sci.
Shyna A., Ushadevi Amma C., Ansamma John, Chandrasekharan Kesavadas, Bejoy Thomas
2021 J jnl
An Approach Towards Physics Informed Lung Ultrasound Image Scoring Neural Network for Diagnostic Assistance in COVID-19.
CoRR
Mahesh Raveendranatha Panicker, Yale Tung Chen, Gayathri Malamal, Madhavanunni A. N, Kiran Vishnu Narayan, Chandrasekharan Kesavadas, A. P. Vinod
2021 B conf
Employing Acoustic Features To Aid Neural Networks Towards Platform Agnostic Learning In Lung Ultrasound Imaging.
ICIP
Mahesh Raveendranatha Panicker, Yale Tung Chen, M. Gayathri, A. N. Madhavanunni, Kiran Vishnu Narayan, Chandrasekharan Kesavadas, A. P. Vinod
2021 J jnl
Multi-Res-Attention UNet: A CNN Model for the Segmentation of Focal Cortical Dysplasia Lesions from Magnetic Resonance Images.
IEEE J. Biomed. Health Informatics
Edwin Thomas, Pawan S. Jogi, Shushant Kumar, Anmol Horo, S. Niyas, S. Vinayagamani, Chandrasekharan Kesavadas, Jeny Rajan
2021 J jnl
Segmentation of focal cortical dysplasia lesions from magnetic resonance images using 3D convolutional neural networks.
Biomed. Signal Process. Control.
S. Niyas, S. Chethana Vaisali, Iwrin Show, T. G. Chandrika, S. Vinayagamani, Chandrasekharan Kesavadas, Jeny Rajan
2021 J jnl
Sub-cortical structure segmentation database for young population.
CoRR
Jayanthi Sivaswamy, Alphin J. Thottupattu, Mythri V, Raghav Mehta, R. Sheelakumari, Chandrasekharan Kesavadas
2020 J jnl
An improved nonlocal maximum likelihood estimation method for denoising magnetic resonance images with spatially varying noise levels.
Pattern Recognit. Lett.
P. V. Sudeep, Palanisamy Ponnusamy, Chandrasekharan Kesavadas, Jeny Rajan
2019 J jnl
Automatic detection and localization of Focal Cortical Dysplasia lesions in MRI using fully convolutional neural network.
Biomed. Signal Process. Control.
K. M. Bijay Dev, Pawan S. Jogi, S. Niyas, S. Vinayagamani, Chandrasekharan Kesavadas, Jeny Rajan
2019 J jnl
Functional Connectivity of Language Regions of Stroke Patients with Expressive Aphasia During Real-Time Functional Magnetic Resonance Imaging Based Neurofeedback.
Brain Connect.
Sreedharan Sujesh, Karumattu Manattu Arun, P. N. Sylaja, Chandrasekharan Kesavadas, Ranganatha Sitaram
2019 J jnl
SWI post processing using granularity controlled edge-preserved denoising of multichannel GRE images.
Int. J. Imaging Syst. Technol.
Sreekanth Madhusoodhanan, Chandrasekharan Kesavadas, Joseph Suresh Paul
2017 J jnl
A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps.
Signal Image Video Process.
P. V. Sudeep, Palanisamy Ponnusamy, Chandrasekharan Kesavadas, Jan Sijbers, Arnold J. den Dekker, Jeny Rajan
2015 J jnl
Nonlocal linear minimum mean square error methods for denoising MRI.
Biomed. Signal Process. Control.
P. V. Sudeep, Palanisamy Ponnusamy, Chandrasekharan Kesavadas, Jeny Rajan
2014 — ch.
Application of Swarm Intelligence in Fuzzy Entropy Based Image Segmentation.
Innovations in Intelligent Machines (5)
Krishna Priya Remamany, C. Thangaraj, Chandrasekharan Kesavadas, S. Kannan
2013 — conf
A Genetic Algorithm Optimized Artificial Neural Network for the Segmentation of MR Images in Frontotemporal Dementia.
SEMCCO (2)
R. Sheela Kumari, Tinu Varghese, Chandrasekharan Kesavadas, N. Albert Singh, P. S. Mathuranath
2013 J jnl
Fuzzy entropy-based MR brain image segmentation using modified particle swarm optimization.
Int. J. Imaging Syst. Technol.
Krishna Priya Remamany, C. Thangaraj, Chandrasekharan Kesavadas, S. Kannan
2013 — conf
Longitudinal Evaluation of Structural Changes in Frontotemporal Dementia Using Artificial Neural Networks.
FICTA
R. Sheela Kumari, Tinu Varghese, Chandrasekharan Kesavadas, N. Albert Singh, P. S. Mathuranath
2013 — conf
Partial Fourier reconstruction using subspace projection.
NCVPRIPG
Uma K., Chandrasekharan Kesavadas, Joseph Suresh Paul
2009 J jnl
Focal Cortical Dysplasia (FCD) lesion analysis with complex diffusion approach.
Comput. Medical Imaging Graph.
Jeny Rajan, K. Kannan, Chandrasekharan Kesavadas, Bejoy Thomas
2008 B conf
Does brain react on Indian music? - A functional magnetic resonance imaging study.
IJCNN
J. Satheeshkumar, S. Arumugaperumal, Reghunadhan Rajesh, Chandrasekharan Kesavadas