Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Mechanical measurement system
Reexamination Certificate
1999-05-21
2002-04-09
Hoff, Marc S. (Department: 2857)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Mechanical measurement system
C073S866400
Reexamination Certificate
active
06370480
ABSTRACT:
BACKGROUND OF THE INVENTION
The invention relates generally to the field of ultrasound imaging machines and particularly, to a quantitative analysis system and method for certifying ultrasound medical equipment. More particularly, the invention is related to the use of a quantitative analysis program for testing the resolution capabilities of such imaging machines using imaging phantoms as test objects and returning a set of indices indicating the condition of the imaging machine.
An ultrasound imaging machine is an electronic device including a signal transmission and detection apparatus for producing an ultrasound image. A medical ultrasound imaging machine is used for uninvasive in vivo visualization so that anatomical structures within a body of a patient are displayed and analyzed. Such a machine transmits sound waves of very high frequency (typically 2 MHZ to 10 MHZ) into the patient and then processes echoes reflected from structures in the patient's body. The purpose of the ultrasound imaging machine is to display and/or analyze the return echoes, which are the result of the phenomena of refraction, reflection, scattering absorption and dispersion of radio frequency ultrasonic pressure waves from a tissue medium in the patient's body. The images formed by the return echoes have a granular structure and are described as having a degree of texture or speckle. The ability of the ultrasound imaging machine to produce an image distinguishing a target object in a scanned volume, known as a slice, from the texture in the image produced from adjacent background material, is defined as imaging machine resolution, or image resolution. A target object distinguished from background structure is said to be resolved. A resolved image is typically stored in memory and on storage devices configured to optimize image storage. Resolved images are displayed for visual examination and analysis on a display device, such as a video monitor or a printer.
Image resolution represents a combination of both independent and inter-related factors, to be described in detail below, that contribute to faithful and repeatable reproduction of medical images. Faithful and repeatable image reproduction is a consequence of periodic testing and calibration of the ultrasonic scanning system. Periodic calibration is necessary because medical images are used as part of human diagnostic procedures. To ensure that this is done, in the United States, federal and state requirements have been established, and the American Institute of Ultrasound in Medicine (AIUM) Ultrasound Practice Accreditation Commission has developed guidelines for ultrasound practice accreditation. According to U.S. guidelines and government requirements, each health-care provider using an ultrasound machine must go through an accreditation process to ensure that the instrumentation used for diagnostic procedures meets established standards. Further, each health-care provider must periodically have ultrasound instrumentation serviced and calibrated regularly and must undergo image quality certification according to the manufacturer's specification.
For quality assurance, these guidelines recommend that routine testing and calibration be made with the use of ultrasound test objects known as “phantoms”. A variety of types of commercially available phantoms are currently used for certifying the function of an ultrasonic machine, each emphasizing the evaluation of one or more test parameters. The typical phantom includes a gel having a smooth texture, which mimics human tissue and emphasizes image nonuniformities and artifacts, making such spurious features easier to detect. Commercially available phantoms contain artificial “targets” embedded in the uniform background gel material, which mimic various entities found in the human body, including liver tissue, tumors and cysts. Commercially available phantoms also contain pin targets arranged at precisely defined orientations and distances from each other, and relative to the scanned slice. A pin is a very small, (compared to the resolution of the imaging machine) high reflectance object, that mimics an infinitely small point. Use of pins as targets determines the accuracy of reproduction of vertical and horizontal dimensions and distances. For example, a set of evenly spaced vertical pins and a separate set of evenly spaced horizontal pins are used to measure the horizontal and vertical linearity of an image.
Methods for evaluating the accuracy of an ultrasound image by utilizing a specific set of algorithms that evaluate performance parameters and which report the results for screen display are known in the art. For example, U.S. Pat. No. 5,689,443 discloses a system that stores information about the scanner, about expected performance standards, and the specifications of at least one phantom test object. Information about the phantom test object includes an image of the phantom test object and preset or prestored spatial measurements of features embedded within the phantom test object. The system processes a test image of the phantom test object and compares the results with the stored information about the actual phantom test object, to quantitatively determine the characteristics of the scanner. The system provides for 1) determination of scanner performance for a particular image, 2) calculations for reporting on all images of a test, and 3) storage and subsequent retrieval of previous measurements obtained by the same scanner for comparison and trend analysis. The user selects regions of the phantom test object and directs the system to employ algorithmic techniques to analyze only the selected region for a variety of image characteristics, for example, contrast, resolution and homogeneity.
While the system just described tests an ultrasound image machine by imaging a phantom test object, and provides for comparison of test results with prior results obtained by that same machine, the system does not compare the test results specifically with an optimum, or “gold standard”, image of the phantom test object. Such an optimum, or “gold standard” image is defined as an image obtained by the same model image machine as being tested, wherein the machine is operating optimally according to manufacturer's specifications and under optimum conditions.
In addition, while the system of U.S. Pat. No. 5,689,443 quantifies certain image quality parameters, such as resolution, contrast, and homogeneity, the system does not provide a specific index for each parameter, such that the indices, both individually and in combination, provide a quantitative assessment of the image machine imaging capability. In particular, the system does not arithmetically combine the individual image quality indices to produce one collective index, which could be called an “Image Health Index”. The system does not indicate to the user, in terms of these individual and collective image quality indices, how the current image test results compare with the above-defined “gold standard” image of the same test.
Further, the system of U.S. Pat. No. 5,689,443 does not automatically shift the test image representation until it is in registration with a comparison image representation obtained from storage or from an outside source, and then compare parameters determined from the two image representations.
While algorithms for isolating and analyzing phantom test objects are known in the art, and while some prior art algorithms attempt to quantify subjective image quality, there exists a need for a tool that utilizes known phantoms, in conjunction with a unique set of algorithms, that quantitatively evaluates a test image by using a comprehensive set of relatively subjective image quality criteria to generate a single indicator. Such a tool needs to examine these, and other criteria, in terms of several parameters derived from a test image and a “gold standard” image, and return a set of indices, along with a single index representing an arithmetic combination of all other image quality indices, which indicates the a
Dailey Christopher James
Gupta Rajiv
Zheng Yibin
Breedlove Jill M.
Cabou Christian G.
Hoff Marc S.
Raymond Edward
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