Literature DB >> 33662849

Standardization of neurophysiology signal data into the DICOM® standard.

Jonathan J Halford1, David A Clunie2, Benjamin H Brinkmann3, Dagmar Krefting4, Jan Rémi5, Felix Rosenow6, Aatif Husain7, Franz Fürbass8, J Andrew Ehrenberg9, Silvia Winkler10.   

Abstract

A standard format for neurophysiology data is urgently needed to improve clinical care and promote research data exchange. Previous neurophysiology format standardization projects have provided valuable insights into how to accomplish the project. In medical imaging, the Digital Imaging and Communication in Medicine (DICOM) standard is widely adopted. DICOM offers a unique environment to accomplish neurophysiology format standardization because neurophysiology data can be easily integrated with existing DICOM-supported elements such as video, ECG, and images and also because it provides easy integration into hospital Picture Archiving and Communication Systems (PACS) long-term storage systems. Through the support of the International Federation of Clinical Neurophysiology (IFCN) and partners in industry, DICOM Working Group 32 (WG-32) has created an initial set of standards for routine electroencephalography (EEG), polysomnography (PSG), electromyography (EMG), and electrooculography (EOG). Longer and more complex neurophysiology data types such as high-definition EEG, long-term monitoring EEG, intracranial EEG, magnetoencephalography, advanced EMG, and evoked potentials will be added later. In order to provide for efficient data compression, a DICOM neurophysiology codec design competition will be held by the IFCN and this is currently being planned. We look forward to a future when a common DICOM neurophysiology data format makes data sharing and storage much simpler and more efficient. Published by Elsevier B.V.

Keywords:  DICOM; Electroencephalogram; Electromyogram; Electrooculogram; Polysomnogram; Standards

Year:  2021        PMID: 33662849     DOI: 10.1016/j.clinph.2021.01.019

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  1 in total

1.  EpiBOX: An Automated Platform for Long-Term Biosignal Collection.

Authors:  Ana Sofia Carmo; Mariana Abreu; Ana Luísa Nobre Fred; Hugo Plácido da Silva
Journal:  Front Neuroinform       Date:  2022-05-23       Impact factor: 3.739

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.