Evidence map›Paper›PMID 39508998›Full record

ArticleMedical & biological engineering & computing2025

Mark3D - A semi-automated open-source toolbox for 3D head- surface reconstruction and electrode position registration using a smartphone camera video.

Suranjita Ganguly, Malaaika Mihir Chhaya, Ankita Jain, Aditya Koppula, Mohan Raghavan, Kousik Sarathy Sridharan

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Article in Medical & biological engineering & computing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Suranjita GangulyDepartment of Biomedical Engineering, Indian Institute of Technology, Hyderabad, India.
Malaaika Mihir ChhayaDepartment of Biomedical Engineering, Indian Institute of Technology, Hyderabad, India.
Ankita JainDepartment of Heritage Science and Technology, Indian Institute of Technology, Hyderabad, India.
Aditya KoppulaDepartment of Biomedical Engineering, Indian Institute of Technology, Hyderabad, India.
Mohan RaghavanDepartment of Biomedical Engineering, Indian Institute of Technology, Hyderabad, India.
Kousik Sarathy SridharanDepartment of Biomedical Engineering, Indian Institute of Technology, Hyderabad, India. ks@bme.iith.ac.in.

Funding

Department of Science and Technology - Science and Heritage Research Initiative (DST-SHRI) DST/TDT/SHRI-34/2021Science and Technology Research Board (SERB-SRG) SRG/2019/000847
6 · The paper itself

Abstract

Source localization in EEG necessitates co-registering the EEG sensor locations with the subject's MRI, where EEG sensor locations are typically captured using electromagnetic tracking or 3D scanning of the subject's head with EEG cap, using commercially available 3D scanners. Both methods have drawbacks, where, electromagnetic tracking is slow and immobile, while 3D scanners are expensive. Photogrammetry offers a cost-effective alternative but requires multiple photos to sample the head, with good spatial sampling to adequately reconstruct the head surface. Post-reconstruction, the existing tools for electrode position labelling on the 3D head-surface have limited visual feedback and do not easily accommodate customized montages, which are typical in multi-modal measurements. We introduce Mark3D, an open-source, integrated tool for 3D head-surface reconstruction from phone camera video. It eliminates the need for keeping track of spatial sampling during image capture for video-based photogrammetry reconstruction. It also includes blur detection algorithms, a user-friendly interface for electrode and tracking, and integrates with popular toolboxes such as FieldTrip and MNE Python. The accuracy of the proposed method was benchmarked with the head-surface derived from a commercially available handheld 3D scanner Einscan-Pro + (Shining 3D Inc.,) which we treat as the "ground truth". We used reconstructed head-surfaces of ground truth (G1) and phone camera video (M

Indexed as

HeadImaging, Three-DimensionalSmartphoneVideo RecordingAlgorithmsElectrodesElectroencephalographyHumansMagnetic Resonance ImagingPhotogrammetryCoregistrationEEG source localisationElectroencephalographyHead surface reconstructionPhotogrammetry

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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.