The current study was conducted using iEEG data collected in realistic clinical conditions without channel pre-exclusion. HFOs were investigated with novel features extracted from the entire frequency band, and were correlated with SOZ in different states. The results indicate that automatic HFO detection with unsupervised clustering methods exploring the time-frequency content of raw iEEG can be efficiently used to identify the epileptogenic zone with an accurate and efficient manner.
We believe that image-guided neuronavigation is useful for neurosurgeons who are at the beginning of their PBC learning curve. It may also be an alternative for particular patients with significant anatomic variations that result in an unsuccessful foramen ovale puncture.
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