Image analysis – Applications – Biomedical applications
Reexamination Certificate
1999-07-15
2004-02-17
Mehta, Bhavesh M. (Department: 2625)
Image analysis
Applications
Biomedical applications
C378S020000, C378S064000, C378S163000, C378S177000, C378S205000, C378S207000, C382S131000, C382S151000, C382S195000, C382S283000, C600S414000, C600S426000
Reexamination Certificate
active
06694047
ABSTRACT:
BACKGROUND OF THE INVENTION
The present invention generally relates to an automated system for evaluating image quality of x-ray systems. More particularly, the present invention relates to an automated analysis and measurement of image quality parameters of an x-ray system using one or more x-ray phantoms. Also, the present invention provides automated Region Of Interest (ROI) determination to facilitate image quality parameter measurement.
X-ray systems, such as an image intensifier, storage phosphor plates or digital detectors, typically include an x-ray emitter and an x-ray receiver. A target to be viewed, such as a human body, is arranged between the x-ray emitter and the x-ray receiver. X-rays produced by the emitter travel through the target to reach the receiver. As the x-rays travel from the emitter through the target, internal components of the target may decrease the energy of the x-rays to varying degrees through effects such as the blocking or absorption of some of the x-rays. The blocking or absorption of x-rays within the target causes the received x-ray energy levels to vary. The x-ray receiver receives the x-rays which have traveled through the target. An image of the target is generated at the x-ray receiver. The image produced at the receiver contains regions of light and dark which correspond to the varying intensity levels of the x-rays which have passed through the target.
The x-ray images may be used for many purposes. For instance, internal defects in the target may be detected. Additionally, changes in internal structure or alignment may be determined. Furthermore, the image may show the presence or absence of objects in the target. The information gained from x-ray imaging has applications in many fields, including medicine and manufacturing.
In order to help ensure that x-ray images may be used reliably, it is advantageous to measure and verify the performance of x-ray systems. In particular, it is important to measure and verify the image quality of the x-ray system. Poor image quality may prevent reliable analysis of the x-ray image. For example, a decrease in image contrast quality may yield an unreliable image that is not usable. Additionally, the advent of real-time imaging systems has increased the importance of generating clear, high quality images. X-ray systems with poor or degraded image quality must be re-calibrated to provide a distinct and usable representation of the target.
The verification of x-ray system performance is also important for safety reasons. For example, exposure to high levels of x-ray energy may involve some health risk to humans. Because of the health risk, governmental standards are set for the use of x-ray systems. The level of x-ray energy emitted by an x-ray system may be measured in terms of radiation dosage. Periodic performance evaluation of x-ray systems may ensure that the radiation dosage to which the target is exposed does not exceed regulatory standards.
One device that may be used in the measurement of x-ray system parameters, such as image quality and radiation dosage, is an x-ray phantom. Several types of phantoms exist, including physical replica phantoms and physics-based phantoms. For example, a physical replica phantom may be a physical replica of an x-ray target, such as a human body part. A physics-based phantom may be comprised of various structures affixed to a common base. The structures of a physics-based phantom may possess varying characteristics, such as shape, size, density, and composition. Furthermore, the structures of physics-based phantoms may be constructed from various materials, including metal and plastic.
The structures of physics-based phantoms may affect the intensity of the x-rays which pass through the physics-based phantom. For example, metal structures may block some or most of the x-rays. Additionally, plastic structures may merely provide minimal attenuation of the x-rays. A pattern resulting from the changes in the intensity of received x-rays is represented in an x-ray image. The resulting pattern in the x-ray image may be easy to detect and analyze due to factors such as the contrast produced by the difference in received x-ray intensities.
Currently known phantoms may serve a variety of purposes. For example, phantoms may test performance parameters of the x-ray system. Also, phantoms, combined with radiation probes, may be used to gauge the radiation dosage of x-ray energy emitted by the emitter. Furthermore, phantoms may be used for calibration and image quality assessment.
Typically, physics-based phantoms may be designed to measure one or more parameters of an x-ray system. Different phantoms may produce different patterns of x-ray intensity or attenuation. The different patterns of x-ray intensity or attenuation may be used to measure or test different performance parameters of the x-ray system.
One of the more recent applications of phantoms is as part of a software based evaluation tool. Such a software based tool is disclosed in U.S. Pat. No. 5,841,835 issued to Aufrichtig et al. (“Aufrichtig”). Aufrichtig has a software component that may add in the assessment and calibration of an x-ray system. Iterative calibration tests may be performed using the software component. The results of iterative calibration tests performed by the software component may be compiled to show analysis, such as trending and aggregation, of the results of the x-ray system calibration tests. As iterative calibration of an x-ray system continues, the software component may automatically adjust the x-ray system parameters.
However, the Aufrichtig software component assumes that a particular phantom is being used for measuring image quality parameters of the x-ray system. If a plurality of phantoms are used, the software may need to be manually configured to react to each different phantom. The extra step of configuring the software component for each x-ray phantom may reintroduce additional human interaction in measurements. Additionally, the configuration of the software component for each x-ray phantom may increase the amount of time necessary to measure the image quality of an x-ray system.
Thus, a need has long existed for an image quality evaluation system able to automatically determine image components on any of multiple phantoms. Additionally, a need has long existed for an automated image quality evaluation system that provides self-alignment and measuring. Additionally, a need has long existed for an automated, cost-effective system for measuring critical image quality parameters using any of multiple phantoms. The preferred embodiments of the present invention address these needs and other concerns with past systems.
SUMMARY OF THE INVENTION
A method and apparatus are provided for automated x-ray system parameter evaluation. A grayscale x-ray image is imported to an image processor which processed the image to determine image components. A histogram of the image is created, then a threshold in the histogram is determined and the imported image is binarized with respect to the threshold. Next, connected component (“blob”) analysis is used to determine image components. The image components in the imported image are then compared to a phantom template of expected components. The system next locates landmarks in the imported image corresponding to expected physical structures. The landmarks may include a perimeter ring, vertical and horizontal line segments, and fiducials. The system uses the landmarks to locate Regions of Interest (ROIs) where measurement of the x-ray system parameters takes place. Finally, the x-ray system parameters are measured in the identified ROIs. A coupon sub-phantom may be used to measure the horizontal or vertical Modulation Transfer Function (MTF).
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Aufrichtig Richard
Farrokhnia Farshid
Kump Kenneth Scott
Tokman Alexander Y.
Dellapenna Michael A.
Desire Gregory
General Electric Company
McAndrews Held & Malloy Ltd.
Mehta Bhavesh M.
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