Ukash Nakarmi

According to our database, Ukash Nakarmi authored at least 25 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Adaptive Extensions of Unbiased Risk Estimators for Unsupervised Magnetic Resonance Image Denoising.

Reeshad Khan, John Gauch, Ukash Nakarmi

CoRR, 2024

Towards an Algebraic Framework For Approximating Functions Using Neural Network Polynomials.

Shakil Rafi, Joshua Lee Padgett, Ukash Nakarmi

CoRR, 2024

Learning From Oversampling: A Systematic Exploitation of Oversampling to Address Data Scarcity Issues in Deep Learning- Based Magnetic Resonance Image Reconstruction.

Ibsa Jalata, Reeshad Khan, Ukash Nakarmi

IEEE Access, 2024

DeepLIR: Attention-Based Approach for Mask-Based Lensless Image Reconstruction.

Arpan Poudel, Ukash Nakarmi

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2024

2023

When System Model Meets Image Prior: An Unsupervised Deep Learning Architecture for Accelerated Magnetic Resonance Imaging.

Ibsa Jalata, Ukash Nakarmi

Proceedings of the Advances in Visual Computing - 18th International Symposium, 2023

On Training Model Bias of Deep Learning based Super-resolution Frameworks for Magnetic Resonance Imaging.

Mamata Shrestha, Nian Wang, Ukash Nakarmi

Proceedings of the IEEE EMBS International Conference on Biomedical and Health Informatics, 2023

2022

Kernel Regression Imputation in Manifolds Via Bi-Linear Modeling: The Dynamic-MRI Case.

Konstantinos Slavakis, Gaurav N. Shetty, Loris Cannelli, Gesualdo Scutari, Ukash Nakarmi, Leslie Ying

IEEE Trans. Computational Imaging, 2022

BrainVGAE: End-to-End Graph Neural Networks for Noisy fMRI Dataset.

Quan Mai, Ukash Nakarmi, Miaoqing Huang

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

2021

Parallel MRI Reconstruction Using Broad Learning System.

Yuchou Chang, Ukash Nakarmi

Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

2020

Bi-Linear Modeling of Data Manifolds for Dynamic-MRI Recovery.

Gaurav N. Shetty, Konstantinos Slavakis, Abhishek Bose, Ukash Nakarmi, Gesualdo Scutari, Leslie Ying

IEEE Trans. Medical Imaging, 2020

Acceleration of three-dimensional diffusion magnetic resonance imaging using a kernel low-rank compressed sensing method.

Chaoyi Zhang, Tanzil Mahmud Arefin, Ukash Nakarmi, Choong-Heon Lee, Hongyu Li, Dong Liang, Jiangyang Zhang, Leslie Ying

NeuroImage, 2020

Spectral Decomposition in Deep Networks for Segmentation of Dynamic Medical Images.

Edgar A. Rios Piedra, Morteza Mardani, Frank Ong, Ukash Nakarmi, Joseph Y. Cheng, Shreyas Vasanawala

CoRR, 2020

Multi-scale Unrolled Deep Learning Framework for Accelerated Magnetic Resonance Imaging.

Ukash Nakarmi, Joseph Y. Cheng, Edgar P. Rios, Morteza Mardani, John M. Pauly, Leslie Ying, Shreyas S. Vasanawala

Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Diagnostic Image Quality Assessment and Classification in Medical Imaging: Opportunities and Challenges.

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

Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Kernel Bi-Linear Modeling for Reconstructing Data on Manifolds: The Dynamic-MRI Case.

Gaurav N. Shetty, Konstantinos Slavakis, Ukash Nakarmi, Gesualdo Scutari, Leslie Ying

Proceedings of the 28th European Signal Processing Conference, 2020

2019

KerNL: Kernel-Based Nonlinear Approach to Parallel MRI Reconstruction.

Jingyuan Lyu, Ukash Nakarmi, Dong Liang, Jinhua Sheng, Leslie Ying

IEEE Trans. Medical Imaging, 2019

2018

Kernel and Manifold Framework for Magnetic Resonance Imaging.

Ukash Nakarmi

PhD thesis, 2018

MLS: Joint manifold-learning and sparsity-aware framework for highly accelerated dynamic magnetic resonance imaging.

Ukash Nakarmi, Konstantinos Slavakis, Leslie Ying

Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

2017

A Kernel-Based Low-Rank (KLR) Model for Low-Dimensional Manifold Recovery in Highly Accelerated Dynamic MRI.

Ukash Nakarmi, Yanhua Wang, Jingyuan Lyu, Dong Liang, Leslie Ying

IEEE Trans. Medical Imaging, 2017

M-MRI: A manifold-based framework to highly accelerated dynamic magnetic resonance imaging.

Ukash Nakarmi, Konstantinos Slavakis, Jingyuan Lyu, Leslie Ying

Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Bi-Linear modeling of manifold-data geometry for Dynamic-MRI recovery.

Konstantinos Slavakis, Gaurav N. Shetty, Abhishek Bose, Ukash Nakarmi, Leslie Ying

Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

2016

Accelerating dynamic magnetic resonance imaging by nonlinear sparse coding.

Ukash Nakarmi, Yihang Zhou, Jingyuan Lyu, Konstantinos Slavakis, Leslie Ying

Proceedings of the 13th IEEE International Symposium on Biomedical Imaging, 2016

2015

Dynamic magnetic resonance imaging using compressed sensing with self-learned nonlinear dictionary (NL-D).

Ukash Nakarmi, Yanhua Wang, Jingyuan Lyu, Leslie Ying

Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015

2012

BCS: Compressive sensing for binary sparse signals.

Ukash Nakarmi, Nazanin Rahnavard

Proceedings of the 31st IEEE Military Communications Conference, 2012

2011

Joint wideband spectrum sensing in frequency overlapping cognitive radio networks using distributed compressive sensing.

Ukash Nakarmi, Nazanin Rahnavard

Proceedings of the MILCOM 2011, 2011