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Akshay S. Chaudhari

6 papers hereh-index 2146 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author6

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.LG1
  • eess.SP1
same name
  • Akshay S. Chaudhari — 16 papers, h 7
  • Akshay S. Chaudhari — 14 papers, h 30
  • Akshay S. Chaudhari — 10 papers, h 8
  • Akshay S. Chaudhari — 3 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedDeep Learning for Accelerated and Robust MRI Reconstruction: a Review

6 citations · 6 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

Diffusion MRI Transformer with a Diffusion Space Rotary Positional Embedding (D-RoPE)

Gustavo Chau Loo Kung, Mohammad Abbasi, Camila Blank +6

Diffusion Magnetic Resonance Imaging (dMRI) plays a critical role in studying microstructural changes in the brain. It is, therefore, widely used in clinical practice; yet progress…

cs.CV2026

Learning Generalizable 3D Medical Image Representations from Mask-Guided Self-Supervision

Yunhe Gao, Yabin Zhang, Chong Wang +5

Foundation models have transformed vision and language by learning general-purpose representations from large-scale unlabeled data, yet 3D medical imaging lacks analogous approache…

cs.CV2025

Efficient Noise Calculation in Deep Learning-based MRI Reconstructions

Onat Dalmaz, Arjun D. Desai, Reinhard Heckel +3

Accelerated MRI reconstruction involves solving an ill-posed inverse problem where noise in acquired data propagates to the reconstructed images. Noise analyses are central to MRI…

cs.CV2024

Enhance the Image: Super Resolution using Artificial Intelligence in MRI

Ziyu Li, Zihan Li, Haoxiang Li +5

This chapter provides an overview of deep learning techniques for improving the spatial resolution of MRI, ranging from convolutional neural networks, generative adversarial networ…

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