Aniket Pramanik

According to our database, Aniket Pramanik authored at least 14 papers between 2019 and 2023.

Collaborative distances:

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

2023

ENSURE: A General Approach for Unsupervised Training of Deep Image Reconstruction Algorithms.

Hemant Kumar Aggarwal, Aniket Pramanik, Maneesh John, Mathews Jacob

IEEE Trans. Medical Imaging, April, 2023

Memory-Efficient Model-Based Deep Learning With Convergence and Robustness Guarantees.

Aniket Pramanik, M. Bridget Zimmerman, Mathews Jacob

IEEE Trans. Computational Imaging, 2023

Adapting model-based deep learning to multiple acquisition conditions: Ada-MoDL.

Aniket Pramanik, Sampada Bhave, Saurav Sajib, Samir D. Sharma, Mathews Jacob

CoRR, 2023

Accelerated Parallel MRI Using Memory Efficient and Robust Monotone Operator Learning (MOL).

Aniket Pramanik, Mathews Jacob

Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

2022

Stable and memory-efficient image recovery using monotone operator learning (MOL).

Aniket Pramanik, Mathews Jacob

CoRR, 2022

Multimodal Super Resolution with Dual Domain Loss and Gradient Guidance.

Anitha Priya Krishnan, Roshan Reddy Upendra, Aniket Pramanik, Zhuang Song, Richard A. D. Carano

Proceedings of the Simulation and Synthesis in Medical Imaging, 2022

Improved Model Based Deep Learning Using Monotone Operator Learning (Mol).

Aniket Pramanik, Mathews Jacob

Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

Joint Calibrationless Reconstruction and Segmentation of Parallel MRI.

Aniket Pramanik, Mathews Jacob

Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

2021

Joint Calibrationless Reconstruction and Segmentation of Parallel MRI.

Aniket Pramanik, Xiaodong Wu, Mathews Jacob

CoRR, 2021

Reconstruction and Segmentation of Parallel MR Data Using Image Domain Deep-SLR.

Aniket Pramanik, Mathews Jacob

Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Ensure: Ensemble Stein's Unbiased Risk Estimator for Unsupervised Learning.

Hemant Kumar Aggarwal, Aniket Pramanik, Mathews Jacob

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Deep Generalization of Structured Low-Rank Algorithms (Deep-SLR).

Aniket Pramanik, Hemant Kumar Aggarwal, Mathews Jacob

IEEE Trans. Medical Imaging, 2020

Calibrationless Parallel MRI Using Model Based Deep Learning (C-MODL).

Aniket Pramanik, Hemant Kumar Aggarwal, Mathews Jacob

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

2019

Off-The-Grid Model Based Deep Learning (O-Modl).

Aniket Pramanik, Hemant Kumar Aggarwal, Mathews Jacob

Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019