13 citations · 13 across the 5 of their papers we have counts for
5 papers
DCE-FORMER: A Transformer-based Model With Mutual Information And Frequency-based Loss Functions For Early And Late Response Prediction In Prostate DCE-MRI
Sadhana S, Sriprabha Ramanarayanan, Arunima Sarkar +3
Dynamic Contrast Enhanced Magnetic Resonance Imaging aids in the detection and assessment of tumor aggressiveness by using a Gadolinium-based contrast agent (GBCA). However, GBCA i…
HyperCoil-Recon: A Hypernetwork-based Adaptive Coil Configuration Task Switching Network for MRI Reconstruction
Sriprabha Ramanarayanan, Mohammad Al Fahim, Rahul G. S. +3
Parallel imaging, a fast MRI technique, involves dynamic adjustments based on the configuration i.e. number, positioning, and sensitivity of the coils with respect to the anatomy u…
Generalizing Supervised Deep Learning MRI Reconstruction to Multiple and Unseen Contrasts using Meta-Learning Hypernetworks
Sriprabha Ramanarayanan, Arun Palla, Keerthi Ram +1
Meta-learning has recently been an emerging data-efficient learning technique for various medical imaging operations and has helped advance contemporary deep learning models. Furth…
Generalizable Deep Learning Method for Suppressing Unseen and Multiple MRI Artifacts Using Meta-learning
Arun Palla, Sriprabha Ramanarayanan, Keerthi Ram +1
Magnetic Resonance (MR) images suffer from various types of artifacts due to motion, spatial resolution, and under-sampling. Conventional deep learning methods deal with removing a…
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…