Vikram Venkatraghavan
Vikram Venkatraghavan
Biomedical Imaging Group Rotterdam, Erasmus MC, Rotterdam, The Netherlands
Verified email at erasmusmc.nl
Title
Cited by
Cited by
Year
Automated oral cancer identification using histopathological images: a hybrid feature extraction paradigm
MMR Krishnan, V Venkatraghavan, UR Acharya, M Pal, RR Paul, LC Min, ...
Micron 43 (2-3), 352-364, 2012
632012
Trajectories of imaging markers in brain aging: the Rotterdam Study
EJ Vinke, M de Groot, V Venkatraghavan, S Klein, WJ Niessen, MA Ikram, ...
Neurobiology of Aging 71, 32-40, 2018
552018
Disease progression timeline estimation for Alzheimer's disease using discriminative event based modeling
V Venkatraghavan, EE Bron, WJ Niessen, S Klein, ...
NeuroImage 186, 518-532, 2019
262019
Systems for detecting and tracking of objects and co-registration
V Venkatraghavan, R Subramaniyan, G Dutta
US Patent App. 14/823,635, 2016
142016
A discriminative event based model for Alzheimer’s disease progression modeling
V Venkatraghavan, EE Bron, WJ Niessen, S Klein
International Conference on Information Processing in Medical Imaging, 121-133, 2017
132017
The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up
RV Marinescu, NP Oxtoby, AL Young, EE Bron, AW Toga, MW Weiner, ...
arXiv preprint arXiv:2002.03419, 2020
92020
Modified radon transform for texture analysis
V Venkatraghavan, S Rekha, J Chatterjee, AK Ray
2011 Annual IEEE India Conference, 1-4, 2011
92011
Multi-study validation of data-driven disease progression models to characterize evolution of biomarkers in Alzheimer's disease
D Archetti, S Ingala, V Venkatraghavan, V Wottschel, AL Young, M Bellio, ...
NeuroImage: Clinical 24, 101954, 2019
82019
Systems for linear mapping of lumens
V Venkatraghavan, R Subramaniyan
US Patent App. 14/535,204, 2015
82015
Generic framework for organ localization in CT and MR images
V Venkatraghavan, S Ranjan
2011 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), 1-7, 2011
52011
Shape orientation pattern
V Venkatraghavan, M Agarwal, AK Roy
IEEE Signal Processing Letters 16 (8), 711-714, 2009
52009
Semantic analysis of 3D anatomical medical images for sub-image retrieval
V Venkatraghavan, S Ranjan
MICCAI International Workshop on Medical Content-Based Retrieval for …, 2011
42011
Statistical tools for evaluating classification efficacy of feature extraction techniques
D Sheet, V Venkatraghavan, A Suveer, H Garud, J Chatterjee, ...
Second International Conference on Digital Image Processing 7546, 75461B, 2010
32010
Event-based modeling with high-dimensional imaging biomarkers for estimating spatial progression of dementia
V Venkatraghavan, F Dubost, EE Bron, WJ Niessen, M de Bruijne, S Klein, ...
International Conference on Information Processing in Medical Imaging, 169-180, 2019
22019
Modelling the cascade of biomarker changes in GRN-related frontotemporal dementia
JL Panman, V Venkatraghavan, EL van der Ende, RME Steketee, ...
Journal of Neurology, Neurosurgery & Psychiatry 92 (5), 494-501, 2021
2021
Analyzing the effect of APOE on Alzheimer’s disease progression using an event-based model for stratified populations
V Venkatraghavan, S Klein, L Fani, LS Ham, H Vrooman, MK Ikram, ...
NeuroImage 227, 117646, 2021
2021
The sequence of structural, functional and cognitive changes in multiple sclerosis
I Dekker, MM Schoonheim, V Venkatraghavan, AJC Eijlers, I Brouwer, ...
NeuroImage: Clinical 29, 102550, 2021
2021
Cross-Cohort Generalizability of Deep and Conventional Machine Learning for MRI-based Diagnosis and Prediction of Alzheimer's Disease
EE Bron, S Klein, JM Papma, LC Jiskoot, V Venkatraghavan, J Linders, ...
arXiv preprint arXiv:2012.08769, 2020
2020
Modelling the cascade of biomarker changes in progranulin‐related frontotemporal dementia: Neuroimaging/Optimal neuroimaging measures for tracking disease progression
V Venkatraghavan, JL Panman, EL van der Ende, R Steketee, LC Jiskoot, ...
Alzheimer's & Dementia 16, e040934, 2020
2020
Deep versus conventional machine learning for MRI‐based diagnosis and prediction of Alzheimer’s disease: Neuroimaging/Optimal neuroimaging measures for early detection
EE Bron, V Venkatraghavan, J Linders, WJ Niessen, S Klein
Alzheimer's & Dementia 16, e040957, 2020
2020
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