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Abhejit Rajagopal
Abhejit Rajagopal
Verified email at ucsf.edu - Homepage
Title
Cited by
Cited by
Year
Plasmonic field confinement for separate absorption-multiplication in InGaAs nanopillar avalanche photodiodes
AC Farrell, P Senanayake, CH Hung, G El-Howayek, A Rajagopal, ...
Scientific reports 5 (1), 17580, 2015
262015
Understanding and Visualizing Generalization in UNets
A Rajagopal, VC Madala, TA Hope, P Larson
Medical Imaging with Deep Learning, 665-681, 2021
82021
Nonlinear electrocardiographic imaging using polynomial approximation networks
A Rajagopal, V Radzicki, H Lee, S Chandrasekaran
APL bioengineering 2 (4), 2018
72018
Federated learning with research prototypes: Application to multi-center MRI-based detection of prostate cancer with diverse histopathology
A Rajagopal, E Redekop, A Kemisetti, R Kulkarni, S Raman, K Sarma, ...
Academic radiology 30 (4), 644-657, 2023
6*2023
Synthetic PET via domain translation of 3-D MRI
A Rajagopal, Y Natsuaki, K Wangerin, M Hamdi, H An, JJ Sunderland, ...
IEEE transactions on radiation and plasma medical sciences 7 (4), 333-343, 2022
62022
Generation of synthetic megavoltage CT for MRI‐only radiotherapy treatment planning using a 3D deep convolutional neural network
JE Scholey, A Rajagopal, EG Vasquez, A Sudhyadhom, PEZ Larson
Medical physics 49 (10), 6622-6634, 2022
62022
A path to qualification of PET/MRI scanners for multicenter brain imaging studies: evaluation of MRI-based attenuation correction methods using a patient phantom
C Catana, R Laforest, H An, F Boada, T Cao, D Faul, B Jakoby, FP Jansen, ...
Journal of Nuclear Medicine 63 (4), 615-621, 2022
62022
Noise reduction in intracranial pressure signal using causal shape manifolds
A Rajagopal, RB Hamilton, F Scalzo
Biomedical signal processing and control 28, 19-26, 2016
62016
Machine-learning-based denoising of doppler ultrasound blood flow and intracranial pressure signal
F Scalzo, A Rajagopal
US Patent App. 16/034,623, 2019
52019
Presurgical 68Ga-PSMA-11 Positron Emission Tomography for Biochemical Recurrence Risk Assessment: A Follow-up Analysis of a Multicenter Prospective Phase 3 Imaging Trial
L Djaïleb, WR Armstrong, D Thompson, A Gafita, A Farolfi, A Rajagopal, ...
European Urology 84 (6), 588-596, 2023
42023
Synthesizing complex-valued multicoil mri data from magnitude-only images
N Deveshwar, A Rajagopal, S Sahin, E Shimron, PEZ Larson
Bioengineering 10 (3), 358, 2023
42023
High-Dimensional Polynomial Approximation with Applications in Imaging and Recognition
A Rajagopal
University of California, Santa Barbara, 2019
42019
Fast Algorithms for Displacement and Low-Rank Structured Matrices
S Chandrasekaran, N Govindarajan, A Rajagopal
arXiv preprint arXiv:1807.03437, 2018
42018
Neuropass: A secure neural password based on EEG
A Rajagopal, AC Nguyen, DM Briggs
Biomedical Engineering, 2013
42013
Harmonization of PET image reconstruction parameters in simultaneous PET/MRI
R Laforest, M Khalighi, Y Natsuaki, A Rajagopal, D Chandramohan, ...
EJNMMI physics 8 (1), 75, 2021
3*2021
Enhanced PET/MRI reconstruction via dichromatic interpolation of domain-translated zero-dose PET
A Rajagopal, N Dwork, TA Hope, PEZ Larson
Medical Imaging 2021: Physics of Medical Imaging 11595, 1127-1135, 2021
32021
Deep learning-based mr-derived pet prediction for patient-conforming pet phantoms
A Rajagopal, A Leynes, SS James, R Laforest, P Larson, T Hope
Journal of Nuclear Medicine 61 (supplement 1), 1417-1417, 2020
32020
Towards deep iterative-reconstruction algorithms for computed tomography (CT) applications
A Rajagopal, N Stier, J Dey, MA King, S Chandrasekaran
Medical Imaging 2019: Physics of Medical Imaging 10948, 1222-1232, 2019
32019
Deep algorithms: designs for networks
A Rajagopal, S Chandrasekaran, HN Mhaskar
arXiv preprint arXiv:1806.02003, 2018
32018
Physics-driven deep learning for pet/mri
A Rajagopal, AP Leynes, N Dwork, JE Scholey, TA Hope, PEZ Larson
arXiv preprint arXiv:2206.06788, 2022
22022
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Articles 1–20