6 citations · 6 across the 6 of their papers we have counts for
6 papers
Fast Voxelwise SNR Estimation for Iterative MRI Reconstructions
Onat Dalmaz, Daniel Abraham, Alexander R. Toews +3
Purpose: To develop a fast, general-purpose framework for voxelwise noise characterization in linear and nonlinear iterative MRI reconstructions, recovering the image-domain noise…
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…
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…
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…
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…
Deep Learning for Accelerated and Robust MRI Reconstruction: a Review
Reinhard Heckel, Mathews Jacob, Akshay Chaudhari +2
Deep learning (DL) has recently emerged as a pivotal technology for enhancing magnetic resonance imaging (MRI), a critical tool in diagnostic radiology. This review paper provides…