Energy-efficient high-fidelity image reconstruction with memristor arrays for medical diagnosis

• Published in: Nature communications Vol. 14; no. 1; pp. 2276 - 10
• Main Authors: Zhao, Han, Liu, Zhengwu, Tang, Jianshi, Gao, Bin, Qin, Qi, Li, Jiaming, Zhou, Ying, Yao, Peng, Xi, Yue, Lin, Yudeng, Qian, He, Wu, Huaqiang
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 20.04.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 59/57; 639/166/985; 639/166/987; 639/925/927/1007; Accuracy; Algorithms; Arrays; Artificial neural networks; Computed tomography; Computer Graphics; Data processing; Diagnosis; Energy efficiency; Fourier transforms; Graphics processing units; Humanities and Social Sciences; Image processing; Image Processing, Computer-Assisted - methods; Image reconstruction; Image segmentation; Magnetic resonance imaging; Mapping; Medical diagnosis; Medical imaging; Memristors; multidisciplinary; Neural networks; Science; Science (multidisciplinary); Software; Tomography, X-Ray Computed

Medical imaging is an important tool for accurate medical diagnosis, while state-of-the-art image reconstruction algorithms raise critical challenges in massive data processing for high-speed and high-quality imaging. Here, we present a memristive image reconstructor (MIR) to greatly accelerate imag...