| Deblurring for spiral real‐time MRI using convolutional neural networks Y Lim, Y Bliesener, S Narayanan, KS Nayak Magnetic resonance in medicine 84 (6), 3438-3452, 2020 | 43 | 2020 |
| A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images Y Lim, A Toutios, Y Bliesener, Y Tian, SG Lingala, C Vaz, T Sorensen, ... Scientific data 8 (1), 187, 2021 | 39 | 2021 |
| Joint arterial input function and tracer kinetic parameter estimation from undersampled dynamic contrast‐enhanced MRI using a model consistency constraint Y Guo, SG Lingala, Y Bliesener, RM Lebel, Y Zhu, KS Nayak Magnetic resonance in medicine 79 (5), 2804-2815, 2018 | 27 | 2018 |
| Efficient DCE-MRI parameter and uncertainty estimation using a neural network Y Bliesener, J Acharya, KS Nayak IEEE transactions on medical imaging 39 (5), 1712-1723, 2019 | 22 | 2019 |
| Tracer kinetic models as temporal constraints during brain tumor DCE‐MRI reconstruction SG Lingala, Y Guo, Y Bliesener, Y Zhu, RM Lebel, M Law, KS Nayak Medical physics 47 (1), 37-51, 2020 | 19 | 2020 |
| Impact of (k, t) sampling on DCE MRI tracer kinetic parameter estimation in digital reference objects Y Bliesener, SG Lingala, JP Haldar, KS Nayak Magnetic resonance in medicine 83 (5), 1625-1639, 2020 | 14 | 2020 |
| Radiofrequency transmit calibration: A multi‐center evaluation of vendor‐provided radiofrequency transmit mapping methods Y Bliesener, X Zhong, Y Guo, M Boss, R Bosca, H Laue, C Chung, K Sung, ... Medical physics 46 (6), 2629-2637, 2019 | 7 | 2019 |
| Pseudo Test-Retest Evaluation of Millimeter-Resolution Whole-Brain Dynamic Contrast-enhanced MRI in Patients with High-Grade Glioma Y Bliesener, RM Lebel, J Acharya, R Frayne, KS Nayak Radiology 300 (2), 410-420, 2021 | 4 | 2021 |
| Method for joint arterial input function and tracer kinetic parameter estimation in accelerated DCE-MRI using a model consistency constraint KS Nayak, Y Bliesener, Y Guo, Y Zhu, SG Lingala, RM Lebel US Patent 11,982,726, 2024 | 3 | 2024 |
| Sparse precontrast T1 mapping for high‐resolution whole‐brain DCE‐MRI Z Zhu, RM Lebel, Y Bliesener, J Acharya, R Frayne, KS Nayak Magnetic Resonance in Medicine 86 (4), 2234-2249, 2021 | 3 | 2021 |
| Method for video-based patch-wise vector quantized auto-encoder codebook learning for video anomaly detection S Qu, Q Cheng, Y Bliesener, J Lee US Patent App. 18/074,195, 2024 | 1 | 2024 |
| Tracer kinetic models as temporal constraints during DCE-MRI reconstruction S Goud Lingala, Y Guo, RM Lebel, Y Zhu, Y Bliesener, M Law, KS Nayak arXiv e-prints, arXiv: 1707.07569, 2017 | 1 | 2017 |
| Comparison of (k, t) sampling schemes for DCE MRI pharmacokinetic parameter estimation Y Bliesener, SG Lingala, JP Haldar, KS Nayak ISMRM 25th Sci. Sess 10, 1909, 2017 | 1 | 2017 |
| System and method for multi-stage display circuit input design Y Bliesener, S Qu, Z Wang US Patent App. 18/326,951, 2024 | | 2024 |
| 14‐4: Efficient Multi‐stage Bayesian Optimization for Optimal Display Circuit Input Signal Design Y Bliesener, Z Wang, S Qu, J Park, J Lee SID Symposium Digest of Technical Papers 54 (1), 178-181, 2023 | | 2023 |
| Deblurring for spiral real-time MRI using convolutional neural networks (vol 84, pg 3438, 2020) Y Lim, Y Bliesener, S Narayanan, KS Nayak MAGNETIC RESONANCE IN MEDICINE 85 (3), 1742-1742, 2021 | | 2021 |
| Joint arterial input function and tracker kinetic parameter estimation from under-sampled DCE-MRI using a model consistency constraint Y Guo, SG Lingala, Y Bliesener, RM Lebel, Y Zhu, KS Nayak Magnetic resonance in medicine 79 (5), 2804, 2018 | | 2018 |
| Test-retest Repeatability of High-resolution Whole-brain DCE-MRI in High-grade Glioma Patients Z Zhu, Y Bliesener, F Chow, J Acharya, KS Nayak | | |
| An open dataset for speech production real-time MRI: raw data, synchronized audio, and images Y Lim, A Toutios, Y Bliesener, Y Tian, KS Nayak, S Narayanan | | |
| High-resolution T Mapping of High-grade Glioma Z Zhu, J Acharya, Y Bliesener, RM Lebel, R Frayne, KS Nayak | | |
Krishna S NayakProfessor of Electrical and Computer Engineering, University of Southern California在 usc.edu 的电子邮件经过验证
