Centre National De La Recherche Scientifique

Columbia University

Université Paris Diderot-Paris 7

Institute Telecom-telecom Paris Tech

Centre National De La Recherche Scientifique-cnrs

Institut Telecom/telecom Paristech

Elsa Angelini

Julie Delon

Andrew F Laine

Emmanuel Mandonnet

A method for quantifying the development of pathologies involving changes in volume of a body represented via an imaging technique, including normalizing gray levels by a midway technique for two images Iand Irepresenting the same scene, resulting in two normalized images I'and I&#x2032;; calculating a map of signed differences between the two normalized images I&#x2032;and I&#x2032;; and performing one or more statistical tests based on the assumption of a Gaussian distribution of the gray levels for healthy tissues in the normalized images I&#x2032;and I&#x2032;and/or in the calculated difference map. Advantageously, results of two or more of the tests can be combined for a more specific characterization of the development.

Method for characterizing the development of pathologies involving changes in volumes of bodies, notably tumors

Treatment and mitigation or reduction of noise effects in noisy image data and data sets is described. Various aspects include treatment of noisy data with brushlet transforms and thresholding operations along with a favorable sequence of spatial and temporal processing and thresholding. Hard and minimax thresholding operators mitigate the noise in the image data. In medical applications this can be useful in removing noise that impairs diagnosis and treatment of patient conditions. In one application, cardiac function is better studied and understood through improved imaging of the heart and cardiac structures. In an exemplary case, a favorable sequence including spatial filtering using a brushlet filter, spatial thresholding of brushlet coefficients, then temporal filtering (first in the time domain then in the frequency domain) and thresholding of temporal coefficients yields an acceptable denoised image data set.

Spatio-temporal treatment of noisy images using brushlets

Growing community of inventors

Paris, France

Elsa Angelini