An Energy-Efficient Accelerator for Medical Image Reconstruction From Implicit Neural Representation
Author:
Affiliation:
1. School of Information Science and Technology, ShanghaiTech University, Shanghai, China
Funder
Shanghai Rising-Star Program
Central Guided Local Science and Technology Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Hardware and Architecture
Link
http://xplorestaging.ieee.org/ielx7/8919/10089883/10004486.pdf?arnumber=10004486
Reference37 articles.
1. GQNA: Generic Quantized DNN Accelerator With Weight-Repetition-Aware Activation Aggregating
2. SMORE: A Self-Supervised Anti-Aliasing and Super-Resolution Algorithm for MRI Using Deep Learning
3. Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks
4. CT Super-Resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble (GAN-CIRCLE)
5. IREM: High-Resolution Magnetic Resonance Image Reconstruction via Implicit Neural Representation
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