Optimal Broadband Noise Matching to Inductive Sensors: Application to Magnetic Particle Imaging
| Autor: | Greig C. Scott, Di Xiao, Neerav Dixit, Beliz Gunel, Steven M. Conolly, Bo Zheng, Patrick W. Goodwill, Wencong Zhang, Kuan Lu |
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| Rok vydání: | 2017 |
| Předmět: |
Diagnostic Imaging
Engineering Scanner Biomedical Engineering 02 engineering and technology Signal-To-Noise Ratio Article 030218 nuclear medicine & medical imaging Magnetics 03 medical and health sciences 0302 clinical medicine Magnetic particle imaging Broadband Electronic engineering Animals Telemetry Electrical and Electronic Engineering Inductive sensor Amplifiers Electronic business.industry Amplifier Bandwidth (signal processing) Detector 021001 nanoscience & nanotechnology Low-noise amplifier 0210 nano-technology business Wireless Technology |
| Zdroj: | IEEE Transactions on Biomedical Circuits and Systems. 11:1041-1052 |
| ISSN: | 1940-9990 1932-4545 |
| Popis: | Inductive sensor-based measurement techniques are useful for a wide range of biomedical applications. However, optimizing the noise performance of these sensors is challenging at broadband frequencies, owing to the frequency-dependent reactance of the sensor. In this work, we describe the fundamental limits of noise performance and bandwidth for these sensors in combination with a low-noise amplifier. We also present three equivalent methods of noise matching to inductive sensors using transformer-like network topologies. Finally, we apply these techniques to improve the noise performance in magnetic particle imaging, a new molecular imaging modality with excellent detection sensitivity. Using a custom noise-matched amplifier, we experimentally demonstrate an 11-fold improvement in noise performance in a small animal magnetic particle imaging scanner. |
| Databáze: | OpenAIRE |
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