We developed a method to distinguish bursts and suppressions for EEG burst suppression from the treatments of status epilepticus, employing the joint time-frequency domain. We obtained the feature used in the proposed method from the joint use of the time and frequency domains, and we estimated the decision as to whether the measured EEG was a burst segment or suppression segment by the maximum likelihood estimation. We evaluated the performance of the proposed method in terms of its accordance with the visual scores and estimation of the burst suppression ratio. The accuracy was higher than the sole use of the time or frequency domains, as well as conventional methods conducted in the time domain. In addition, probabilistic modeling provided a more simplified optimization than conventional methods. Burst suppression quantification necessitated precise burst suppression segmentation with an easy optimization; therefore, the excellent discrimination and the easy optimization of burst suppression by the proposed method appear to be beneficial.
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Publication date: Available online 4 January 2018 Source: European Journal of Radiology Author(s): Peiyao Zhang, Jing Wang, Qin Xu, Zhen...
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Medicine by Alexandros G. Sfakianakis,Anapafseos 5 Agios Nikolaos 72100 Crete Greece,00302841026182, Butyric Acid from Probiotic Staphyloco...
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Does CBD Oil Lower Blood Pressure? This article was originally published at SundayScaries." Madeline Taylor POSTED ON January 13, 20...
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Medicine by Alexandros G. Sfakianakis,Αλέξανδρος Γ. Σφακιανάκης A Novel Technique for Endoscopic Repair of Large Anterior Skull Base Defect...
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BACKGROUND AND PURPOSE: Lesion load is a common biomarker in multiple sclerosis, yet it has historically shown modest association with cl...
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Abstract The development of focused ion beam-scanning electron microscopy (FIB-SEM) techniques has allowed high-resolution 3D imaging of n...
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Vol.48 No.2 from #AlexandrosSfakianakis via Alexandros G.Sfakianakis on Inoreader http://ift.tt/1S2Z7n2 via IFTTT
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