US 7,610,155 B2Granted

Methods for processing spectral data for enhanced embryo classification

AssigneeWeyerhaeuser NR Company

InventorsRoger Timmis, Mitchell R. Toland

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Abstract

A method is disclosed for classifying plant embryos according to their quality using a logistic regression model. First, sets of image or spectral data are acquired from plant embryos of known quality, respectively. Second, each of the acquired sets of image or spectral data is associated with one of multiple class labels according to the corresponding embryo's known quality. Third the sets of image or spectral data values are filtered to provide filtered image or spectral data values. Fourth, a classification algorithm, e.g., a logistic regression analysis is applied to the filtered data values and their corresponding class labels to develop a classification model. Fifth, image or spectral data are acquired from a plant embryo of unknown quality, and filtered data values are derived therefrom. Sixth, the classification model is applied to the filtered data values for the plant embryo of unknown quality to classify the same.

Claims13

Dependent claims

A method for developing a classification model for classifying plant embryos according to their quality, the method comprising:

(a) receiving sets of spectral data of plant embryos of known quality, each set of spectral data of a plant embryo of known quality being associated with one of multiple class labels according to the known quality of the corresponding embryo from which the set of spectral data of the plant embryo of known quality is obtained;
(b) filtering, using a plurality of filters, the received sets of spectral data of the plant embryos of known quality to provide sets of filtered spectral data values of the plant embryos of known quality, each set of filtered spectral data values of the plant embryo of known quality being associated with one of the multiple class labels according to the known quality of the corresponding embryo from which the set of filtered spectral data values of the plant embryo of known quality values is derived, wherein the filtering comprises:
(i) for each filter, linearly combining spectral data values over a band of wavelengths to provide linearly combined spectral data values;
(ii) identifying those filters that best discriminate between different embryo class labels based on cumulative distribution functions estimated at each wavelength for each filter for each embryo class label, to provide sets of best-filtered spectral data values;
and
(iii) reducing the sets of best-filtered spectral data values based on the Smirnov statistics calculated between pairs of embryo class labels at each wavelength for each filter, to provide the sets of filtered spectral data values;
(c) applying a classification algorithm to the sets of filtered spectral data values of the plant embryos of known quality and their corresponding class labels to develop the classification model;
and
(d) outputting the developed classification model to a user for use in classifying embryos according to their quality, wherein all of the steps are performed on a computer.

6 more elements

An article comprising a computer-readable storage medium including computer-executable instructions, wherein the instructions when loaded onto a computer perform the steps comprising:

(a) receiving sets of filtered spectral data of plant embryos of known quality, each set of filtered spectral data of a plant embryo of known quality being associated with one of multiple class labels according to the known quality of the corresponding embryo from which the set of filtered spectral data of the plant embryo of known quality is obtained, wherein the sets of filtered spectral data are provided based on filtering using a plurality of filters comprising the steps including:
(i) for each filter, linearly combining spectral data over a band of wavelengths to provide linearly combined spectral data;
(ii) identifying those filters that best discriminate between different embryo class labels based on cumulative distribution functions estimated at each wavelength for each filter for each embryo class label, to provide sets of best-filtered spectral data;
and
(iii) reducing the sets of best-filtered spectral data based on the Smirnov statistics calculated between pairs of embryo class labels at each wavelength for each filter, to provide the sets of filtered spectral data;
(b) applying a classification algorithm to the sets of filtered spectral data of embryos of known quality and their corresponding class labels to develop a classification model;
and
(c) outputting the developed classification model to a user for use in classifying embryos according to their quality.

5 more elements

Dependencies are inferred from the claim text.

Facts

Application: 11/297,919Filed 8 Dec 2005 · us provisional application
Priority: 28 Dec 2004
Published: US 2006/0143731 A129 Jun 2006
Granted: 27 Oct 2009
Term ends: Not estimatedThe source records don’t support an estimate.

Classification3 codes

G06V 20/695
Microscopic objects, e.g. biological cells or cellular parts: preprocessing, e.g. image segmentation
G06V 20/698
Microscopic objects, e.g. biological cells or cellular parts: matching; Classification
G06V
Image and video recognition

Family

Application60/639,995Us provisional application · filed 28 Dec 2004
US 2006/0143731 A1Pre-grant publication · published 29 Jun 2006
US 7,610,155 B2This patent

From the US filing history. Foreign family members aren’t listed.

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