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Found 5 papers, 1 papers with code
Advancing low-field MRI with a universal denoising imaging transformer: Towards fast and high-quality imaging
Recent developments in low-field (LF) magnetic resonance imaging (MRI) systems present remarkable opportunities for affordable and widespread MRI access.
Convolutional Neural Network Transformer (CNNT) for Fluorescence Microscopy image Denoising with Improved Generalization and Fast Adaptation
Previous methods are based on convolutional neural networks (CNNs) which generally require more time-consuming training of separate models for each new imaging experiment, impairing the applicability and generalization.
Inline AI: Open-source Deep Learning Inference for Cardiac MR
The model was loaded and inference on incoming images were performed while the data acquisition was ongoing, and results were sent back to scanner.
Imaging transformer for MRI denoising with the SNR unit training: enabling generalization across field-strengths, imaging contrasts, and anatomy
The ability to recover MRI signal from noise is key to achieve fast acquisition, accurate quantification, and high image quality.
MTAG: Modal-Temporal Attention Graph for Unaligned Human Multimodal Language Sequences
Human communication is multimodal in nature; it is through multiple modalities such as language, voice, and facial expressions, that opinions and emotions are expressed.
