1.1k citations · 1.3k across the 15 of their papers we have counts for
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A unified deeplearning framework for contrast-phase-specific virtual monochromatic imaging
Antony Jerald, Hemant K Aggarwal, Brian Nett +4
Dual-energy CT (DECT) enables virtual monochromatic imaging (VMI) and improved contrast resolution, but its clinical adoption is limited by hardware complexity and cost. In this wo…
Display Field-Of-View Agnostic Robust CT Kernel Synthesis Using Model-Based Deep Learning
Hemant Kumar Aggarwal, Antony Jerald, Phaneendra K. Yalavarthy +2
In X-ray computed tomography (CT) imaging, the choice of reconstruction kernel is crucial as it significantly impacts the quality of clinical images. Different kernels influence sp…
LSST: Learned Single-Shot Trajectory and Reconstruction Network for MR Imaging
Hemant Kumar Aggarwal, Sudhanya Chatterjee, Dattesh Shanbhag +2
Single-shot magnetic resonance (MR) imaging acquires the entire k-space data in a single shot and it has various applications in whole-body imaging. However, the long acquisition t…
Deep Image Prior using Stein's Unbiased Risk Estimator: SURE-DIP
Maneesh John, Hemant Kumar Aggarwal, Qing Zou +1
Deep learning algorithms that rely on extensive training data are revolutionizing image recovery from ill-posed measurements. Training data is scarce in many imaging applications,…
Model-Based Deep Learning for Reconstruction of Joint k-q Under-sampled High Resolution Diffusion MRI
Merry P. Mani, Hemant K. Aggarwal, Sanjay Ghosh +1
We propose a model-based deep learning architecture for the reconstruction of highly accelerated diffusion magnetic resonance imaging (MRI) that enables high resolution imaging. Th…
Label Consistent Transform Learning for Hyperspectral Image Classification
Jyoti Maggu, Hemant K. Aggarwal, Angshul Majumdar
This work proposes a new image analysis tool called Label Consistent Transform Learning (LCTL). Transform learning is a recent unsupervised representation learning approach; we add…
Discriminative Robust Deep Dictionary Learning for Hyperspectral Image Classification
Vanika Singhal, Hemant K. Aggarwal, Snigdha Tariyal +1
This work proposes a new framework for deep learning that has been particularly tailored for hyperspectral image classification. We learn multiple levels of dictionaries in a robus…
Impulse Denoising From Hyper-Spectral Images: A Blind Compressed Sensing Approach
Angshul Majumdar, Naushad Ansari, Hemant Aggarwal +1
In this work we propose a technique to remove sparse impulse noise from hyperspectral images. Our algorithm accounts for the spatial redundancy and spectral correlation of such ima…
Dynamic MRI using deep manifold self-learning
Abdul Haseeb Ahmed, Hemant Aggarwal, Prashant Nagpal +1
We propose a deep self-learning algorithm to learn the manifold structure of free-breathing and ungated cardiac data and to recover the cardiac CINE MRI from highly undersampled me…
J-MoDL: Joint Model-Based Deep Learning for Optimized Sampling and Reconstruction
Hemant Kumar Aggarwal, Mathews Jacob
Modern MRI schemes, which rely on compressed sensing or deep learning algorithms to recover MRI data from undersampled multichannel Fourier measurements, are widely used to reduce…