858 citations · 885 across the 11 of their papers we have counts for
7 papers · 1 filter
KDPhys: An Attention Guided 3D to 2D Knowledge Distillation for Real-time Video-Based Physiological Measurement
Nicky Nirlipta Sahoo, VS Sachidanand, Matcha Naga Gayathri +4
Camera-based physiological monitoring, such as remote photoplethysmography (rPPG), captures subtle variations in skin optical properties caused by pulsatile blood volume changes us…
A deep cascade of ensemble of dual domain networks with gradient-based T1 assistance and perceptual refinement for fast MRI reconstruction
Balamurali Murugesan, Sriprabha Ramanarayanan, Sricharan Vijayarangan +3
Deep learning networks have shown promising results in fast magnetic resonance imaging (MRI) reconstruction. In our work, we develop deep networks to further improve the quantitati…
MAC-ReconNet: A Multiple Acquisition Context based Convolutional Neural Network for MR Image Reconstruction using Dynamic Weight Prediction
Sriprabha Ramanarayanan, Balamurali Murugesan, Keerthi Ram +1
Convolutional Neural network-based MR reconstruction methods have shown to provide fast and high quality reconstructions. A primary drawback with a CNN-based model is that it lacks…
KD-MRI: A knowledge distillation framework for image reconstruction and image restoration in MRI workflow
Balamurali Murugesan, Sricharan Vijayarangan, Kaushik Sarveswaran +2
Deep learning networks are being developed in every stage of the MRI workflow and have provided state-of-the-art results. However, this has come at the cost of increased computatio…
DC-WCNN: A deep cascade of wavelet based convolutional neural networks for MR Image Reconstruction
Sriprabha Ramanarayanan, Balamurali Murugesan, Keerthi Ram +1
Several variants of Convolutional Neural Networks (CNN) have been developed for Magnetic Resonance (MR) image reconstruction. Among them, U-Net has shown to be the baseline archite…
A context based deep learning approach for unbalanced medical image segmentation
Balamurali Murugesan, Kaushik Sarveswaran, Vijaya Raghavan S +3
Automated medical image segmentation is an important step in many medical procedures. Recently, deep learning networks have been widely used for various medical image segmentation…
Recon-GLGAN: A Global-Local context based Generative Adversarial Network for MRI Reconstruction
Balamurali Murugesan, Vijaya Raghavan S, Kaushik Sarveswaran +2
Magnetic resonance imaging (MRI) is one of the best medical imaging modalities as it offers excellent spatial resolution and soft-tissue contrast. But, the usage of MRI is limited…