Image analysis – Learning systems – Neural networks
Reexamination Certificate
2008-09-30
2008-09-30
Bella, Matthew C. (Department: 2624)
Image analysis
Learning systems
Neural networks
C382S159000, C382S128000
Reexamination Certificate
active
11121745
ABSTRACT:
Methods for identifying and quantifying recurrent and deterministic patterns in digital images are provided. The methods, which are based on Recurrence Quantification Analysis (RQA), generate similarity or dissimilarity distance matrices for digital images that may be used to calculate a variety of quantitative characteristics for the images. Also provided are methods for identifying and imaging spatial distributions of time variable signals generated from dynamic systems. In these methods a time variable signal is recorded for a plurality of area or volume elements into which a dynamic system has been sectioned and RQA is used to calculate one or more RQA variables for each of the area or volume elements, which may then be used to generate a two or three dimensional image displaying the spatial distribution of the RQA variables across the system.
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Bianciardi Marta
Colosimo Alfredo
Giuliani Alessandro
Hagberg Gisela
Sirabella Paolo
Bella Matthew C.
Foley & Lardner LLP
Tucker Wesley
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