3 citations · 6 across the 4 of their papers we have counts for
5 papers
Advancing low-field MRI with a universal denoising imaging transformer: Towards fast and high-quality imaging
Zheren Zhu, Azaan Rehman, Xiaozhi Cao +5
Recent developments in low-field (LF) magnetic resonance imaging (MRI) systems present remarkable opportunities for affordable and widespread MRI access. A robust denoising method…
Convolutional Neural Network Transformer (CNNT) for Fluorescence Microscopy image Denoising with Improved Generalization and Fast Adaptation
Azaan Rehman, Alexander Zhovmer, Ryo Sato +8
Deep neural networks have been applied to improve the image quality of fluorescence microscopy imaging. Previous methods are based on convolutional neural networks (CNNs) which gen…
Inline AI: Open-source Deep Learning Inference for Cardiac MR
Hui Xue, Rhodri H Davies, James Howard +8
Cardiac Magnetic Resonance (CMR) is established as a non-invasive imaging technique for evaluation of heart function, anatomy, and myocardial tissue characterization. Quantitative…
Imaging transformer for MRI denoising with the SNR unit training: enabling generalization across field-strengths, imaging contrasts, and anatomy
Hui Xue, Sarah Hooper, Azaan Rehman +11
The ability to recover MRI signal from noise is key to achieve fast acquisition, accurate quantification, and high image quality. Past work has shown convolutional neural networks…
MTAG: Modal-Temporal Attention Graph for Unaligned Human Multimodal Language Sequences
Jianing Yang, Yongxin Wang, Ruitao Yi +5
Human communication is multimodal in nature; it is through multiple modalities such as language, voice, and facial expressions, that opinions and emotions are expressed. Data in th…