The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Apr. 09, 2002

Filed:

May. 21, 1999
Applicant:
Inventors:

Rajiv Gupta, New York, NY (US);

Yibin Zheng, Rexford, NY (US);

Christopher James Dailey, Sommerville, SC (US);

Assignee:

General Electric Company, Schenectady, NY (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G01B 7/008 ;
U.S. Cl.
CPC ...
G01B 7/008 ;
Abstract

An analysis system and method provide for quantitatively evaluating image quality characteristics of an ultrasound imaging machine that evaluates at least one image representation of a standard phantom acquired by the image machine. The machine under test by comparing acquired parameters with prestored values, and returning a determined set of image quality indices, along with a single index representing an arithmetic combination of all other image quality indices, which indicate the accuracy of the test image relative to a “gold standard” that has been pre-established for the model of imaging machine under investigation. The system, which includes a computer-programmed set of instructions and data, optionally includes at least one standard phantom. The image quality indices, or metrics, quantitatively represent an evaluation of a test image using a set of relatively subjective criteria that include homogeneity, contrast, signal attenuation and penetration of depth, pin to background ratio in near and far-field, axial and lateral resolution, modulation transfer function, and geometric distortion, and axial and lateral linearity. These image quality indices are determined by specific algorithms and then combined to form an image health index. The image health index and the individual component indices are compared to a gold standard set of indices obtained from an equivalent imaging machine operating under optimum conditions and settings.


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