Predicting RF-Induced Heating for Deep Brain Stimulator System Using an Artificial Neural Network
Author:
Affiliation:
1. Electrical and Computer Engineering University of Houston,Houston,USA
2. High Performance Computing for MRI Safety,Jasper,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9970567/9970555/09970664.pdf?arnumber=9970664
Reference17 articles.
1. Fast Prediction of RF-induced Heating for Sacral Neuromodulation System Exposed to Multi-Channel 2 RF Field at 3T MRI
2. A Technique to Evaluate MRI-Induced Electric Fields at the Ends of Practical Implanted Lead
3. Reducing the Radiofrequency-Induced Heating of Active Implantable Medical Device with Load Impedance Modification
4. The Virtual Family—development of surface-based anatomical models of two adults and two children for dosimetric simulations
5. Evaluation of the RF-induced lead-tip heating of AIMDs using a Volume-Weighed Tissue-Cluster Model for 1.5T MRI
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1. Influence of Implantation Depth of Semi-Implantable Devices in Different Tissues on Radio-frequency Heating;2024 4th International Conference on Neural Networks, Information and Communication (NNICE);2024-01-19
2. A workflow for predicting radiofrequency‐induced heating around bilateral deep brain stimulation electrodes in MRI;Medical Physics;2023-12-28
3. Patient-Specific RF-induced Heating Prediction for Deep Brain Stimulator System under Parallel Transmit at 3T with Machine Learning Method;2023 IEEE Symposium on Electromagnetic Compatibility & Signal/Power Integrity (EMC+SIPI);2023-07-29
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