ArticleJournal of neural engineering2019
iEEGview: an open-source multifunction GUI-based Matlab toolbox for localization and visualization of human intracranial electrodes.
Article in Journal of neural engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 39 citations in OpenAlex.
- Motor imagery-based neural networks for assisting tetraplegic patients.Medical & biological engineering & computing · 2025Article
- Fusion of FDG and FMZ PET Reduces False-Positives in Predicting Epileptogenic Zone.AJNR. American journal of neuroradiology · 2025Article
- Simultaneous invasive and non-invasive recordings in humans: A novel Rosetta stone for deciphering brain activity.Journal of neuroscience methods · 2024Review
- Anatomical registration of intracranial electrodes. Robust model-based localization and deformable smooth brain-shift compensation methods.Journal of neuroscience methods · 2024Review
- iEEG-recon: A fast and scalable pipeline for accurate reconstruction of intracranial electrodes and implantable devices.Epilepsia · 2024Article
- YAEL: Your Advanced Electrode Localizer.eNeuro · 2023Article
- Efficient volume-based localization and automatic labeling of intracranial depth electrodes.Annals of translational medicine · 2023Article
- Spontaneous State Detection Using Time-Frequency and Time-Domain Features Extracted From Stereo-Electroencephalography Traces.Frontiers in neuroscience · 2022Article
- Modeling intracranial electrodes. A simulation platform for the evaluation of localization algorithms.Frontiers in neuroinformatics · 2022Article
- Hybrid Fluoroscopic and Neurophysiological Targeting of Responsive Neurostimulation of the Rolandic Cortex.Operative neurosurgery (Hagerstown, Md.) · 2021Article
- Efficient automated localization of ECoG electrodes in CT images via shape analysis.International journal of computer assisted radiology and surgery · 2021Article
- Investigating Data Cleaning Methods to Improve Performance of Brain-Computer Interfaces Based on Stereo-Electroencephalography.Frontiers in neuroscience · 2021Article
- LeGUI: A Fast and Accurate Graphical User Interface for Automated Detection and Anatomical Localization of Intracranial Electrodes.Frontiers in neuroscience · 2021Article
- BrainQuake: An Open-Source Python Toolbox for the Stereoelectroencephalography Spatiotemporal Analysis.Frontiers in neuroinformatics · 2021Article
- Self-Related Stimuli Decoding With Auditory and Visual Modalities Using Stereo-Electroencephalography.Frontiers in neuroscience · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 3 countries.
Funding
Abstract
objectiveThe precise localization of intracranial electrodes is a fundamental step relevant to the analysis of intracranial electroencephalography (iEEG) recordings in various fields. With the increasing development of iEEG studies in human neuroscience, higher requirements have been posed on the localization process, resulting in urgent demand for more integrated, easy-operation and versatile tools for electrode localization and visualization. With the aim of addressing this need, we develop an easy-to-use and multifunction toolbox called iEEGview, which can be used for the localization and visualization of human intracranial electrodes. APPROACH: iEEGview is written in Matlab scripts and implemented with a GUI. From the GUI, by taking only pre-implant MRI and post-implant CT images as input, users can directly run the full localization pipeline including brain segmentation, image co-registration, electrode reconstruction, anatomical information identification, activation map generation and electrode projection from native brain space into common brain space for group analysis. Additionally, iEEGview implements methods for brain shift correction, visual location inspection on MRI slices and computation of certainty index in anatomical label assignment. MAIN
resultsAll the introduced functions of iEEGview work reliably and successfully, and are tested by images from 28 human subjects implanted with depth and/or subdural electrodes. SIGNIFICANCE: iEEGview is the first public Matlab GUI-based software for intracranial electrode localization and visualization that holds integrated capabilities together within one pipeline. iEEGview promotes convenience and efficiency for the localization process, provides rich localization information for further analysis and offers solutions for addressing raised technical challenges. Therefore, it can serve as a useful tool in facilitating iEEG studies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.