Literature DB >> 16028553

Quantifying motion in video recordings of neonatal seizures by regularized optical flow methods.

Nicolaos B Karayiannis1, Bindu Varughese, Guozhi Tao, James D Frost, Merrill S Wise, Eli M Mizrahi.   

Abstract

This paper presents the development of regularized optical flow computation methods and an evaluation of their performance in the extraction of quantitative motion information from video recordings of neonatal seizures. A general formulation of optical flow computation is presented and a mathematical framework for the development of practical tools for computing optical flow is outlined. In addition, this paper proposes an alternative formulation of the optical flow problem that relies on a discrete approximation of a family of quadratic functionals. These regularized optical flow computation methods are used to extract motion strength signals from video recordings of neonatal seizures.

Entities:  

Mesh:

Year:  2005        PMID: 16028553     DOI: 10.1109/tip.2005.849320

Source DB:  PubMed          Journal:  IEEE Trans Image Process        ISSN: 1057-7149            Impact factor:   10.856


  2 in total

1.  Optical Flow Estimation Improves Automated Seizure Detection in Neonatal EEG.

Authors:  Joel R Martin; Paolo G Gabriel; Jeffrey J Gold; Richard Haas; Suzanne L Davis; David D Gonda; Cynthia Sharpe; Scott B Wilson; Nicolas C Nierenberg; Mark L Scheuer; Sonya G Wang
Journal:  J Clin Neurophysiol       Date:  2022-03-01       Impact factor: 2.590

2.  Automated video-based detection of nocturnal motor seizures in children.

Authors:  Anouk van Westrhenen; George Petkov; Stiliyan N Kalitzin; Richard H C Lazeron; Roland D Thijs
Journal:  Epilepsia       Date:  2020-05-07       Impact factor: 5.864

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.