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Publication search results
found 28 matches
- 2024
- Ibsa Jalata, Reeshad Khan, Ukash Nakarmi:
Learning From Oversampling: A Systematic Exploitation of Oversampling to Address Data Scarcity Issues in Deep Learning- Based Magnetic Resonance Image Reconstruction. IEEE Access 12: 97621-97629 (2024) - Arpan Poudel, Ukash Nakarmi:
DeepLIR: Attention-Based Approach for Mask-Based Lensless Image Reconstruction. WACV (Workshops) 2024: 431-439 - Shakil Rafi, Joshua Lee Padgett, Ukash Nakarmi:
Towards an Algebraic Framework For Approximating Functions Using Neural Network Polynomials. CoRR abs/2402.01058 (2024) - Reeshad Khan, John Gauch, Ukash Nakarmi:
Adaptive Extensions of Unbiased Risk Estimators for Unsupervised Magnetic Resonance Image Denoising. CoRR abs/2407.15799 (2024) - 2023
- Mamata Shrestha, Nian Wang, Ukash Nakarmi:
On Training Model Bias of Deep Learning based Super-resolution Frameworks for Magnetic Resonance Imaging. BHI 2023: 1-5 - Ibsa Jalata, Ukash Nakarmi:
When System Model Meets Image Prior: An Unsupervised Deep Learning Architecture for Accelerated Magnetic Resonance Imaging. ISVC (1) 2023: 370-381 - 2022
- Konstantinos Slavakis, Gaurav N. Shetty, Loris Cannelli, Gesualdo Scutari, Ukash Nakarmi, Leslie Ying:
Kernel Regression Imputation in Manifolds Via Bi-Linear Modeling: The Dynamic-MRI Case. IEEE Trans. Computational Imaging 8: 133-147 (2022) - Quan Mai, Ukash Nakarmi, Miaoqing Huang:
BrainVGAE: End-to-End Graph Neural Networks for Noisy fMRI Dataset. BIBM 2022: 3852-3855 - 2021
- Yuchou Chang, Ukash Nakarmi:
Parallel MRI Reconstruction Using Broad Learning System. EMBC 2021: 2704-2707 - 2020
- Chaoyi Zhang, Tanzil Mahmud Arefin, Ukash Nakarmi, Choong-Heon Lee, Hongyu Li, Dong Liang, Jiangyang Zhang, Leslie Ying:
Acceleration of three-dimensional diffusion magnetic resonance imaging using a kernel low-rank compressed sensing method. NeuroImage 210: 116584 (2020) - Gaurav N. Shetty, Konstantinos Slavakis, Abhishek Bose, Ukash Nakarmi, Gesualdo Scutari, Leslie Ying:
Bi-Linear Modeling of Data Manifolds for Dynamic-MRI Recovery. IEEE Trans. Medical Imaging 39(3): 688-702 (2020) - Gaurav N. Shetty, Konstantinos Slavakis, Ukash Nakarmi, Gesualdo Scutari, Leslie Ying:
Kernel Bi-Linear Modeling for Reconstructing Data on Manifolds: The Dynamic-MRI Case. EUSIPCO 2020: 1482-1486 - Jeffrey J. Ma, Ukash Nakarmi, Cedric Yue Sik Kin, Christopher M. Sandino, Joseph Y. Cheng, Ali B. Syed, Peter Wei, John M. Pauly, Shreyas S. Vasanawala:
Diagnostic Image Quality Assessment and Classification in Medical Imaging: Opportunities and Challenges. ISBI 2020: 337-340 - Ukash Nakarmi, Joseph Y. Cheng, Edgar P. Rios, Morteza Mardani, John M. Pauly, Leslie Ying, Shreyas S. Vasanawala:
Multi-scale Unrolled Deep Learning Framework for Accelerated Magnetic Resonance Imaging. ISBI 2020: 1056-1059 - Gaurav N. Shetty, Konstantinos Slavakis, Ukash Nakarmi, Gesualdo Scutari, Leslie Ying:
Kernel Bi-Linear Modeling for Reconstructing Data on Manifolds: The Dynamic-MRI Case. CoRR abs/2002.11885 (2020) - Edgar A. Rios Piedra, Morteza Mardani, Frank Ong, Ukash Nakarmi, Joseph Y. Cheng, Shreyas Vasanawala:
Spectral Decomposition in Deep Networks for Segmentation of Dynamic Medical Images. CoRR abs/2010.00003 (2020) - 2019
- Jingyuan Lyu, Ukash Nakarmi, Dong Liang, Jinhua Sheng, Leslie Ying:
KerNL: Kernel-Based Nonlinear Approach to Parallel MRI Reconstruction. IEEE Trans. Medical Imaging 38(1): 312-321 (2019) - Jeffrey J. Ma, Ukash Nakarmi, Cedric Yue Sik Kin, Christopher M. Sandino, Joseph Y. Cheng, Ali B. Syed, Peter Wei, John M. Pauly, Shreyas Vasanawala:
Diagnostic Image Quality Assessment and Classification in Medical Imaging: Opportunities and Challenges. CoRR abs/1912.02907 (2019) - 2018
- Ukash Nakarmi:
Kernel and Manifold Framework for Magnetic Resonance Imaging. University at Buffalo, New York, USA, 2018 - Ukash Nakarmi, Konstantinos Slavakis, Leslie Ying:
MLS: Joint manifold-learning and sparsity-aware framework for highly accelerated dynamic magnetic resonance imaging. ISBI 2018: 1213-1216 - Gaurav N. Shetty, Konstantinos Slavakis, Abhishek Bose, Ukash Nakarmi, Leslie Ying, Gesualdo Scutari:
Bi-Linear Modeling of Data Manifolds for Dynamic-MRI Recovery. CoRR abs/1812.10617 (2018) - 2017
- Ukash Nakarmi, Yanhua Wang, Jingyuan Lyu, Dong Liang, Leslie Ying:
A Kernel-Based Low-Rank (KLR) Model for Low-Dimensional Manifold Recovery in Highly Accelerated Dynamic MRI. IEEE Trans. Medical Imaging 36(11): 2297-2307 (2017) - Konstantinos Slavakis, Gaurav N. Shetty, Abhishek Bose, Ukash Nakarmi, Leslie Ying:
Bi-Linear modeling of manifold-data geometry for Dynamic-MRI recovery. CAMSAP 2017: 1-5 - Ukash Nakarmi, Konstantinos Slavakis, Jingyuan Lyu, Leslie Ying:
M-MRI: A manifold-based framework to highly accelerated dynamic magnetic resonance imaging. ISBI 2017: 19-22 - 2016
- Ukash Nakarmi, Yihang Zhou, Jingyuan Lyu, Konstantinos Slavakis, Leslie Ying:
Accelerating dynamic magnetic resonance imaging by nonlinear sparse coding. ISBI 2016: 510-513 - 2015
- Ukash Nakarmi, Yanhua Wang, Jingyuan Lyu, Leslie Ying:
Dynamic magnetic resonance imaging using compressed sensing with self-learned nonlinear dictionary (NL-D). ISBI 2015: 331-334 - 2012
- Ukash Nakarmi, Nazanin Rahnavard:
BCS: Compressive sensing for binary sparse signals. MILCOM 2012: 1-5 - 2011
- Ukash Nakarmi, Nazanin Rahnavard:
Joint wideband spectrum sensing in frequency overlapping cognitive radio networks using distributed compressive sensing. MILCOM 2011: 1035-1040
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