Method and apparatus for an improved computer aided diagnosis system

Claim 1

A method of analyzing a medical image to use a CAD system to detect anatomical abnormalities obtained from one of a plurality of original sources, the method comprising: providing a computer-aided detection (CAD) system configured to numerically process a medical image for identifying anatomical abnormalities therein, the CAD system having been trained using a training image set obtained from a first of said original sources; defining a canonical contrast response curve based on the training image set and the first original source; normalizing each medical image such that each medical image conforms to the canonical contrast response curve for image analysis regardless of the original source of the medical image; and numerically processing each of the normalized medical images using the CAD system to identify anatomical abnormalities therein.

Claim 2

A method of analyzing a medical image to use a CAD system to detect anatomical abnormalities obtained from one of a plurality of original sources, the method comprising: providing a computer-aided detection (CAD) system configured to numerically process a medical image for identifying anatomical abnormalities therein, the CAD system having been trained using a training image set obtained from a first of said original sources; defining a canonical contrast response curve based on the training image set and the first original source; normalizing each medical image such that each medical image conforms to the canonical contrast response curve for image analysis regardless of the original source of the medical image; and numerically processing each of the normalized medical images using the CAD system to identify anatomical abnormalities therein.

Claim 8

An apparatus to improve medical imaging comprising: a computer-aided detection (CAD) system configured to numerically process a medical image for identifying anatomical abnormalities therein, the CAD system having been trained using a training image set obtained from a first of said original sources; an image analysis system to define a canonical contrast response curve based on the training image set and the first original source, the image analysis system further to normalize a medical image to conform to the canonical contrast response curve regardless of an original format of the image; and the CAD system further to process the normalized medical image to identify anatomical abnormalities therein, thereby permitting a single analysis algorithm to be used on all images regardless of original source.

Claim 9

An apparatus to improve medical imaging comprising: a computer-aided detection (CAD) system configured to numerically process a medical image for identifying anatomical abnormalities therein, the CAD system having been trained using a training image set obtained from a first of said original sources; an image analysis system to define a canonical contrast response curve based on the training image set and the first original source, the image analysis system further to normalize a medical image to conform to the canonical contrast response curve regardless of an original format of the image; and the CAD system further to process the normalized medical image to identify anatomical abnormalities therein, thereby permitting a single analysis algorithm to be used on all images regardless of original source.

Claim 22

A system comprising: a computer-aided detection (CAD) system configured to numerically process a medical image for identifying anatomical abnormalities therein, the CAD system having been trained using a training image set obtained from a first source; a source of image data, each image in the image data having one of a multiplicity of spatial resolutions and a multiplicity of contrast responses; a preprocessing module to normalize the image by transforming the image data into a “canonical” form with uniform contrast response, overall level and pixel size, the canonical form based on the training image set and the first source; such that the image analyzed by a computer aided diagnosis system has a uniform contrast response regardless of the original source of the image the CAD further to numerically process each of the normalized images to identify anatomical abnormalities therein.

Claim 23

A system comprising: a computer-aided detection (CAD) system configured to numerically process a medical image for identifying anatomical abnormalities therein, the CAD system having been trained using a training image set obtained from a first source; a source of image data, each image in the image data having one of a multiplicity of spatial resolutions and a multiplicity of contrast responses; a preprocessing module to normalize the image by transforming the image data into a “canonical” form with uniform contrast response, overall level and pixel size, the canonical form based on the training image set and the first source; such that the image analyzed by a computer aided diagnosis system has a uniform contrast response regardless of the original source of the image the CAD further to numerically process each of the normalized images to identify anatomical abnormalities therein.

Claim 29

A system comprising: a source of image data; a preprocessing module transforming the medical image into a “canonical” form with a universal contrast response, overall level, and pixel size, such that the contrast response of the medical image is the same as other medical images in said canonical form; a computer-aided detection (CAD) module to process the image data to detect abnormal anatomical features meeting selected criteria and to flag the abnormal anatomical features as suspicious regions; a post-processing module to modify a contrast response curve of the image to increase visibility of the suspicious regions.

Claim 30

A system comprising: a source of image data; a preprocessing module transforming the medical image into a “canonical” form with a universal contrast response, overall level, and pixel size, such that the contrast response of the medical image is the same as other medical images in said canonical form; a computer-aided detection (CAD) module to process the image data to detect abnormal anatomical features meeting selected criteria and to flag the abnormal anatomical features as suspicious regions; a post-processing module to modify a contrast response curve of the image to increase visibility of the suspicious regions.

Claim 32

A system comprising: a source of medical images, each image having one of a multiplicity of spatial resolutions and one of a multiplicity of contrast responses; a preprocessing module transforming the medical image into a “canonical” form with a uniform contrast response, overall level, and pixel size; a CAD module to process the medical image to detect abnormal anatomical features meeting selected criteria and to generate annotation maps identifying image portions corresponding to said abnormal anatomical features; a post-processing module to modify a contrast response curve of the image to increase visibility of suspicious regions associated with the abnormal anatomical features; and a display to selectively display annotation maps at positions corresponding to suspicious regions.

Claim 33

A system comprising: a source of medical images, each image having one of a multiplicity of spatial resolutions and one of a multiplicity of contrast responses; a preprocessing module transforming the medical image into a “canonical” form with a uniform contrast response, overall level, and pixel size; a CAD module to process the medical image to detect abnormal anatomical features meeting selected criteria and to generate annotation maps identifying image portions corresponding to said abnormal anatomical features; a post-processing module to modify a contrast response curve of the image to increase visibility of suspicious regions associated with the abnormal anatomical features; and a display to selectively display annotation maps at positions corresponding to suspicious regions.