Applied Spectral Imaging Ltd.

Nissim Ben-Yosef

Dario Cabib

Robert A Buckwald

Zvi Malik

A method of spectral-morphometric analysis of biological samples, the biological samples including substantially constant components and suspected variable components, the method is effected by following the steps of (a) using a spectral data collection device for collecting spectral data of picture elements of the biological samples; (b) defining a spectral vector associated with picture elements representing a constant component of at least one of the biological samples; (c) using the spectral vector for defining a correcting function being selected such that when operated on spectral vectors associated with picture elements representing other constant components, spectral vectors of the other constant components are modified to substantially resemble the spectral vector; (d) operating the correcting function on spectral vectors associated with at least the variable components for obtaining corrected spectral vectors thereof; and (e) classifying the corrected spectral vectors into classification groups.

Spectral bio-imaging data for cell classification using internal reference

According to the present invention there is provided a spectral bio-imaging methods which can be used for automatic and/or semiautomatic spectrally resolved morphometric classification of cells, the method comprising the steps of (a) preparing a sample to be spectrally imaged, the sample including at least a portion of at least one cell; (b) viewing the sample through an optical device, the optical device being optically connected to an imaging spectrometer, the optical device and the imaging spectrometer being for obtaining a spectrum of each pixel of the sample; (c) classifying each of the pixels into classification groups according to the pixels spectra; and (d) analyzing the classification groups and thereby classifying the at least one cell into a cell class.

Spectral bio-imaging methods for cell classification

A method and hardware for chromosome classification by decorrelation statistical analysis to provide color (spectral) karyotypes and to detect chromosomal aberrations. The method and hardware employ a set of N decorrelation matched filters for chromosome classification. The N decorrelation matched filters are dedicated for extracting decorrelated spectral data from chromosome samples painted according to a specific experimental protocol. The N decorrelation matched filters being described by: ##EQU1## where V.sub.ik min equals minimum V.sub.ik over all i, and V.sub.ik max equals maximum V.sub.ik over all i, and wherein N is an integer greater than two.

Method for chromosome classification by decorrelaiton statistical

A method and hardware for chromosome classification by decorrelation statistical analysis to provide color (spectral) karyotypes and to detect chromosomal aberrations.

Growing community of inventors

Jerusalem, Israel

Nissim Ben-Yosef