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Microwave-Based Stroke Diagnosis Making Global Prehospital Thrombolytic Treatment Possible
Here, we present two different brain diagnostic devices based on microwave technology and the associated two first proof-of-principle measurements that show that the systems can differentiate hemorrhagic from ischemic stroke in acute stroke patients, as well as differentiate hemorrhagic patients from healthy volunteers. The system was based on microwave scattering measurements with an antenna system worn on the head. Measurement data were analyzed with a machine-learning algorithm that is based on training using data from patients with a known condition. Computer tomography images were used as reference. The detection meth...
Source: IEEE Transactions on Biomedical Engineering - October 17, 2014 Category: Biomedical Engineering Source Type: research

Prediction of Hemorrhagic Transformation Severity in Acute Stroke From Source Perfusion MRI
Conclusion: The key contribution of our framework formalize HT prediction as a machine learning problem. Specifically, the model learns to extract imaging markers of HT directly from source PWI images rather than from pre-established metrics. Significance: Predictions visualized in terms of spatial likelihood of HT in various territories of the brain were evaluated against follow-up gradient recalled echo and provide novel insights for neurointerventionalists prior to endovascular therapy.
Source: IEEE Transactions on Biomedical Engineering - August 21, 2018 Category: Biomedical Engineering Source Type: research

Deep-Learning-Enabled Microwave-Induced Thermoacoustic Tomography Based on ResAttU-Net for Transcranial Brain Hemorrhage Detection
Conclusion: The proposed ResAttU-Net-based DL-MITAT method is promising for mitigating the acoustic inhomogeneity issue and performing transcranial brain hemorrhage detection. Significance: This work provides a novel ResAttU-Net-based DL-MITAT paradigm and paves a compelling route for transcranial brain hemorrhage detection as well as other transcranial brain imaging applications.
Source: IEEE Transactions on Biomedical Engineering - July 21, 2023 Category: Biomedical Engineering Source Type: research