Integrated Automatic Detection, Classification and Imaging of High Frequency Oscillations With Stereoelectroencephalography.

ABSTRACT:

Objective

During presurgical evaluation for focal epilepsy patients, the evidence supporting the use of high frequency oscillations (HFOs) for delineating the epileptogenic zone (EZ) increased over the past decade. This study aims to develop and validate an integrated automatic detection, classification and imaging pipeline of HFOs with stereoelectroencephalography (SEEG) to narrow the gap between HFOs quantitative analysis and clinical application.

Methods

The proposed pipeline includes stages of channel inclusion, candidate HFOs detection and automatic labeling with four trained convolutional neural network (CNN) classifiers and HFOs sorting based on occurrence rate and imaging. We first evaluated the initial detector using an open simulated dataset. After that, we validat

SUBMITTER: Zhao B 

PROVIDER: S-EPMC7287040 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature