Ukash Nakarmi

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 24

Top Topics

Image Reconstruction

Medical Imaging

Magnetic Resonance

Spectral Decomposition

Top Venues

IEEE Trans. Medical Imaging

WACV (Workshops)

Publications

Reeshad Khan, John Gauch, Ukash Nakarmi
Adaptive Extensions of Unbiased Risk Estimators for Unsupervised Magnetic Resonance Image Denoising. CoRR (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 (2024)
Arpan Poudel, Ukash Nakarmi
DeepLIR: Attention-Based Approach for Mask-Based Lensless Image Reconstruction. WACV (Workshops) (2024)
Shakil Rafi, Joshua Lee Padgett, Ukash Nakarmi
Towards an Algebraic Framework For Approximating Functions Using Neural Network Polynomials. CoRR (2024)
Ibsa Jalata, Ukash Nakarmi
When System Model Meets Image Prior: An Unsupervised Deep Learning Architecture for Accelerated Magnetic Resonance Imaging. ISVC (1) (2023)
Mamata Shrestha, Nian Wang, Ukash Nakarmi
On Training Model Bias of Deep Learning based Super-resolution Frameworks for Magnetic Resonance Imaging. BHI (2023)
Quan Mai, Ukash Nakarmi, Miaoqing Huang
BrainVGAE: End-to-End Graph Neural Networks for Noisy fMRI Dataset. BIBM (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 (2022)
Yuchou Chang, Ukash Nakarmi
Parallel MRI Reconstruction Using Broad Learning System. EMBC (2021)
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)
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 (2020)
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)
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 (2020)
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)
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) (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. CoRR (2020)
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) (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 (2019)
Ukash Nakarmi, Konstantinos Slavakis, Leslie Ying
MLS: Joint manifold-learning and sparsity-aware framework for highly accelerated dynamic magnetic resonance imaging. ISBI (2018)
Gaurav N. Shetty, Konstantinos Slavakis, Abhishek Bose, Ukash Nakarmi, Leslie Ying, Gesualdo Scutari
Bi-Linear Modeling of Data Manifolds for Dynamic-MRI Recovery. CoRR (2018)
Konstantinos Slavakis, Gaurav N. Shetty, Abhishek Bose, Ukash Nakarmi, Leslie Ying
Bi-Linear modeling of manifold-data geometry for Dynamic-MRI recovery. CAMSAP (2017)
Ukash Nakarmi, Konstantinos Slavakis, Jingyuan Lyu, Leslie Ying
M-MRI: A manifold-based framework to highly accelerated dynamic magnetic resonance imaging. ISBI (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) (2017)
Ukash Nakarmi, Yihang Zhou, Jingyuan Lyu, Konstantinos Slavakis, Leslie Ying
Accelerating dynamic magnetic resonance imaging by nonlinear sparse coding. ISBI (2016)
Ukash Nakarmi, Yanhua Wang, Jingyuan Lyu, Leslie Ying
Dynamic magnetic resonance imaging using compressed sensing with self-learned nonlinear dictionary (NL-D). ISBI (2015)
Ukash Nakarmi, Nazanin Rahnavard
BCS: Compressive sensing for binary sparse signals. MILCOM (2012)
Ukash Nakarmi, Nazanin Rahnavard
Joint wideband spectrum sensing in frequency overlapping cognitive radio networks using distributed compressive sensing. MILCOM (2011)