Role of high resolution in magnetic resonance (MR) imaging: Applications to MR angiography, intracranial T1-weighted imaging, and image interpolation. - Ramesh Venkatesan; E. Mark Haacke (Int. J. Imaging Syst. Technol., 1997)

Magnetic resonance scan-time reduction using echo prediction. - Joseph Suresh Paul; Manu Prasad; Ramesh Venkatesan; Michael Braun (Int. J. Imaging Syst. Technol., 2013)

Acceleration by Deep-Learnt Sharing of Superfluous Information in Multi-contrast MRI. - Sudhanya Chatterjee; Suresh Emmanuel Joel; Ramesh Venkatesan; Dattesh Dayanand Shanbhag (MICCAI (6), 2021)

MCI-HyperNet: A multiple contextual information-based adaptive weight learning network for controllable image reconstruction. - Sriprabha Ramanarayanan; Balamurali Murugesan; Arun Palla; Keerthi Ram; Ramesh Venkatesan; Mohanasankar Sivaprakasam (Neurocomputing, 2023)

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; Keerthi Ram; NagaGayathri Matcha; Suresh Emmanuel Joel; Harsh Agarwal; Ramesh Venkatesan; Mohanasankar Sivaprakasam (ISBI, 2024)

AAD-DCE: An Aggregated Multimodal Attention Mechanism for Early and Late Dynamic Contrast Enhanced Prostate MRI Synthesis. - Divya Bharti; Sriprabha Ramanarayanan; Sadhana S; Kishore Kumar M; Keerthi Ram; Harsh Agarwal; Ramesh Venkatesan; Mohanasankar Sivaprakasam (ICASSP, 2025)

SHFormer: Dynamic spectral filtering convolutional neural network and high-pass kernel generation transformer for adaptive MRI reconstruction. - Sriprabha Ramanarayanan; Rahul G. S.; Mohammad Al Fahim; Keerthi Ram; Ramesh Venkatesan; Mohanasankar Sivaprakasam (Neural Networks, 2025)