Quantifying motion in video recordings of neonatal seizures by regularized optical flow methods.
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.
Karayiannis
Nicolaos B
NB
Department of Electrical and Computer Engineering, University of Houston, Houston, TX 77204-4005, USA.
Varughese
Bindu
B
Tao
Guozhi
G
Frost
James D
JD
Wise
Merrill S
MS
Mizrahi
Eli M
EM
D000465:Algorithms; D001185:Artificial Intelligence; D003196:Computer Graphics; D004831:Epilepsies, Myoclonic / Q000175:diagnosis* / Q000209:etiology / Q000503:physiopathology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007231:Infant, Newborn; D016247:Information Storage and Retrieval / Q000379:methods; D009068:Movement; D009716:Numerical Analysis, Computer-Assisted; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012640:Seizures / Q000150:complications / Q000175:diagnosis* / Q000503:physiopathology*; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013382:Subtraction Technique; D014584:User-Computer Interface