X-ray or gamma ray systems or devices – Specific application – Mammography
Reexamination Certificate
1999-01-25
2001-01-09
Bruce, David V. (Department: 2876)
X-ray or gamma ray systems or devices
Specific application
Mammography
C378S062000, C378S098900
Reexamination Certificate
active
06173034
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates generally to digital xray imaging and, more particularly, to a method of digital mammography that uses dual-energy apparatus and methods for separating a single human breast x-ray image into component images, each representing a single physical substance.
2. The Prior Art
Typical clinical mammography is performed by using x-ray films. Recently, large format two-dimensional semiconductor digital x-ray detector arrays have been available. Currently, regardless of the technology, all of the image information is contained in a single image, acquired through the use of x-rays with a single energy-spectrum. The human breast is comprised of three major substances, the lean tissue, the fat tissue, and microcalcification deposits, and each pixel of such a single image contains a mixture of all three, plus a random scatter component. The size of the contribution from each component is not known in current mammography.
It is well established that the role of the random scatter signal in an x-ray imaging is interference and distortion. The scatter blurs the image, reduces the image contrast, and degrades the image quality. The contribution of scatter in mammography is generally as high as 30% to 60% of the total image signal.
It has also been established by breast cancer research, that the cancer cells have an x-ray attenuation coefficient very close to that of glandular duct which has an average composition of typical lean tissue. Thus, only the lean tissue component provides useful information for the diagnosis of cancer. The direct value of the fat tissue information for the diagnosis is very small. At the same time, the fat tissue or adipose tissue occupies as much as about 50% of the total breast volume and is closely mingled with the lean tissue. Thus, in mammography, the fat tissue signal also acts more as an adverse factor, imposing a strong, irregular pattern to mask the useful information.
The image signal of lean tissue is used for direct determination of breast cancer or other pathological changes. The microcalcification component is an important reference because it has been found that most breast cancer patients have a large amount of microcalcification in breast tissue.
Because of the inability to separate the four basic signal components, the capability of current x-ray imaging for cancer diagnosis has been essentially limited.
The present invention is based on the dual-energy x-ray imaging method disclosed in U.S. Pat. Nos. 5,648,997 and 5,771,269 and U.S. patent application Ser. No. 09/025,926 (the Chao disclosures). In terms of the prior art, the applicability of dual-energy x-ray imaging to mammography is discussed in several journal articles. The method and apparatuses used in these articles are essentially different from the present invention. For example, Chakraborty et al. (An Energy Sensitive Cassette for Dual-Energy Mammography, 16(1) Medical Physics 7 (January/February 1989)) designed a double film cassette to use a “dual-energy subtraction method” for enhancing image contrast. Johns and Yaffe (Theoretical Optimization of Dual-Energy x-Ray Imaging with Application to Mammography, 12(3) Medical Physics 289 (May, June 1985)) conducted experiments using linear detector arrays and linearization approximations for dual energy decomposition. First, the hardware between these references and the Chao disclosures is different; the detectors of the prior art are either film cassettes, linear detector arrays, or stimulable phosphor plates. Using an intermediate digitizing method to convert the analog image data either from x-ray films or from stimulable phosphor plates into a digital format is essentially a semi-quantitative imaging system. The present invention uses two-dimensional large format integrated semiconductor detectors for direct high-accuracy quantitative imaging. Secondly, the dual-energy decomposition in the prior art is invariably based on linearization methods, while the present invention is based on directly solving a dual-energy fundamental equation system in its original form without relying on linearization. Thirdly, the present invention uses imaging hardware which combines scatter removal capability and dual-energy data acquisition in one system.
SUMMARY OF THE INVENTION
An object of the present invention is to provide a method for enhancing the diagnosis value of x-ray images for mammography.
The present invention provides a method for quantitatively separating a breast x-ray image into a number of component images: the scatter image, the fat tissue image, the lean tissue image, and the microcalcification image. The present invention uses dual-energy x-ray imaging system hardware configurations as described in U.S. Pat. Nos. 5,648,997 and 5,771,269 and U.S. patent application Ser. No. 09/025,926 (the Chao disclosures), incorporated herein by reference. The present invention does not provide any new hardware.
As to the method of the present invention, the basic methods for removing scatter and for dual-energy decomposition described in the Chao disclosures are used, and are not an aspect of the present invention. However, the method of the present invention includes significant improvements and is not a simple implementation of these patented methods. To separate the three material composition by using the basic dual-energy method, new procedures are required. The present invention provides a systematic method to achieve decomposition of a breast image into multiple component images according to physical substance.
The method of the present invention is to use the basic method for removal of scatter and the basic method for dual-energy x-ray imaging to first separate a mixed breast image into four basic image components: a scatter image, a lean tissue image, a fat tissue image, and a microcalcification image. “Microcalcification” is used interchangeably with “calcification”. These images are a first order approximation. Then the three material compositions of the human breast are taken into account. In the second order approximation, the microcalcification image, lean tissue image, and fat tissue image are separated so that each contains only a single breast component.
The method of obtaining the first order approximations includes the steps of (a) performing a calibration, as described below, to obtain a pair of numerical relationships for the front detector at the high and low energies for the microcalcification c and the soft tissue s to obtain the functions c=c(D
H
,D
L
) and s=s(D
H
,D
L
), (b) perform a calibration to obtain a pair of numerical relationships for the front detector at the high and low energies for the fat tissue f and the lean tissue g to obtain the functions f=f(D
H
,D
L
) and g=g(D
H
,D
L
), (c) illuminating the subject with x-rays of said average energy level H and of average energy L, (d) acquiring high-resolution images D
fHh
(x,y) and D
fLh
(x,y) from the front detection locations (x,y), where the images are composed of both primary and scatter x-rays, (e) calculating a pair of high-resolution scatter x-ray images D
fSHh
(x,y) and D
fSLh
(x,y), (f) calculating a pair of high-resolution primary x-ray images D
fPHh
(x,y) =D
fHh
(x,y)−D
fSHh
(x,y) and D
fPLh
(x,y)=D
fLh
(x,y)−D
fSLh
(x,y) (g) performing a dual-energy decomposition for the image pair D
fPHh
(x,y) and D
fPLh
(x,y) using the functions c=c(D
H
,D
L
) and s=s(D
H
,D
L
) to obtain two first order approximation material composition images c
1
(x,y) and s
1
(x,y), and (h) performing a dual-energy decomposition for the image pair D
fPHh
(x,y) and D
fPLh
(x,y) using the functions f=f(D
H
,D
L
) and g=g(D
H
,D
L
) to obtain two first order approximation material composition images f
1
(x,y) and g
1
(x,y).
The method of obtaining the second order approximations corrects for microcalcification effects and includes the steps of (a) identifying all microcalcification points c
1
(x
k
,y
k
) and all non-microcalc
Advanced Optical Technologies, Inc.
Bruce David V.
Morse, Altman & Martin
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