Image analysis – Applications – Biomedical applications
Reexamination Certificate
1998-11-10
2002-04-30
Boudreau, Leo (Department: 2721)
Image analysis
Applications
Biomedical applications
Reexamination Certificate
active
06381349
ABSTRACT:
BACKGROUND OF THE INVENTION
The present invention relates to the art of diagnostic nuclear imaging. It finds particular application in conjunction with gamma cameras and single photon emission computed tomography (SPECT), and will be described with particular reference thereto. However, it is to be appreciated that the present invention is also amenable to other like applications.
Diagnostic nuclear imaging, is used to study a radionuclide distribution in a subject. Typically, in SPECT, one or more radiopharmaceuticals or radioisotopes are injected into a subject. The radiopharmaceuticals are commonly injected into the subject's blood stream for imaging the circulatory system or for imaging specific organs which absorb the injected radiopharmaceuticals. One or more gamma or scintillation camera detector heads, typically including a collimator, are placed adjacent to a surface of the subject to monitor and record emitted radiation. The camera heads typically include a scintillation crystal which produces a flash or scintillation of light each time it is struck by radiation emanating from the radioactive dye in the subject. An array of photomultiplier tubes and associated circuitry produce an output signal which is indicative of the (x, y) position of each scintillation on the crystal. Often, the heads are rotated or indexed around the subject to monitor the emitted radiation from a plurality of directions to obtain a plurality of different views. The monitored radiation data from the plurality of views is reconstructed into a three dimensional (3D) image representation of the radiopharmaceutical distribution within the subject.
One of the problems with this imaging technique is that photon absorption and scatter (i.e., Compton scattering) by portions of the subject between the emitting radionuclide and the camera head distort the resultant image. One solution for compensating for photon attenuation is to assume uniform photon attenuation throughout the subject. That is, the subject is assumed to be completely homogenous in terms of radiation attenuation with no distinction made for bone, soft tissue, lung, etc. This enables attenuation estimates to be made based on the surface contour of the subject. Of course, human subjects do not cause uniform radiation attenuation, especially in the chest.
In order to obtain more accurate radiation attenuation measurements, a direct measurement is made using transmission computed tomography techniques. In this technique, radiation is projected from a radiation source through the subject. The transmission radiation is received by detectors at the opposite side. The source and detectors are rotated to collect transmission data concurrently with the emission data through a multiplicity of angles. This transmission data is reconstructed into an image representation or attenuation map using conventional tomography algorithms. The radiation attenuation properties of the subject from the transmission computed tomography image are used to correct for radiation attenuation in the emission data. See, for example, U.S. Pat. Nos. 5,210,421 and 5,559,335, commonly assigned and incorporated herein by reference.
To assure that the radiation comes along a known path through or from the subject, collimators are often placed in front of radiation-receiving faces of the detector heads. The collimators typically include a grid of lead vanes which assure that received radiation is traveling along a path from the subject substantially perpendicular to the radiation-receiving faces of the detector heads.
Other collimators have been developed to “magnify” regions of interest. In a cone-beam collimator, the vanes are tapered or angled such that all the vanes point at a common focal point. Radiation reaching the radiation-receiving faces of the detector heads is constrained by the cone-beam collimator to radiation traveling along divergent paths in two directions such that the entire radiation-receiving face of the detector head is used to examine a relatively small region of interest. This magnification improves the resolution in two planar dimensions. Rather than magnifying in two dimensions, fan-beam collimators have also been developed which magnify in one dimension. That is, the vanes are oriented such that the vanes focus the radiation on a focal line, rather than a focal point.
The collimators introduce a system geometric point response that is spatially varying and deteriorates with distance from the face of the collimator. This results in shape distortions and nonuniform density variations in images reconstructed from projection data obtained from a SPECT imaging system. The system geometric point response is dependant on the point source location and collimator geometry. See, for example, G. L. Zeng, et al., “Three-Dimensional Iterative Reconstruction Algorithms with Attenuation and Geometric Point Response Correction,”
IEEE Trans. Nucl. Sci
., Vol. 38, pp. 693-702, 1991.
Scatter correction is an important factor in reconstructing accurate images from SPECT data. Scatter correction techniques, such as multiple-window subtraction and intrinsic modeling with iterative algorithms, have been under study for many years. In fact, methods have been developed for scatter correction in SPECT. See, for example: Z. Liang, et al., “Simultaneous Compensation for Attenuation, Scatter and Detector response for SPECT Reconstruction in Three Dimensions,”
Phys. Med. Biol
., Vol. 37, pp. 587-603, 1992; A. T. Riaku, et al., “Photon Propagation and Detection in Single-Photon Emission Computed Tomography—an Analytic Approach,”
Med. Phys
., Vol. 21, p. 1311-1321, 1994; A. T. Riaku, et al., “Experimental and Numerical Investigation of the 3D SPECT Photon Detection Kernel for Non-Uniform Attenuating Media,”
Phys. Med. Biol
., Vol. 41, pp. 1167-1189, 1996; and, R. G. Wells, et al., “Experimental Validation of an Analytical Method of Calculating SPECT Projection Data,”
IEEE Trans. Nucl. Sci
., Vol. 44, pp. 1283-1290, 1997. Methods that use multiple acquisition energy windows to estimate the scattered photons and subtract the estimated photons from the projection data have found applications in research and clinical studies. See, for example: B. Axelsson, et al., “Subtraction of Compton-Scattered Photons in Single-Photon Emission Computed Tomography,”
J. Nucl. Med
., Vol. 25, pp. 490-494, 1984; R. J. Jaszczak, et al., “Improved SPECT Quantification Using Compensation for Scattered Photons,”
J. Nucl. Med
., Vol. 25, pp. 893-900, 1984; K. F. Koral, et al., “SPECT Dual-Energy Window Compton Correction: Scatter Multiplier Required for Quantification,”
J. Nucl. Med
., Vol. 31, pp. 90-98, 1990; K. Ogawa, et al., “A Practical Method for Position-Dependent Compton-Scatter Correction in SPECT,”
IEEE Trans. Med. Imag
., Vol. 10, pp. 408-412, 1991; M. A. King, et al., “A Dual Photo-Peak Window Method for Scatter Correction,”
J. Nucl. Med
., Vol. 33, pp. 605-612, 1992; and, D. R. Gilland, et al., “A 3D Model of Non-Uniform Attenuation and Detector Response Compensation for Efficient Reconstruction in SPECT,”
Phys. Med. Biol
., Vol. 39, pp. 547-561, 1994. These pre-processing methods are efficient and effective, but the pre-subtracting methods tend to increase noise and may introduce negative or zero values at locations where projection values are positive. An alternative method to avoid subtraction is to add estimated scatter events to forward projections of the current reconstructed image in an iterative algorithm. See, for example, J. E. Bowsher, et al., “Bayesian Reconstruction and Use of Anatomical a Priori Information for Emission Tomography,”
IEEE Trans. Med. Imag
., Vol. 15, pp. 673-686, 1996. However, subtracting or adding data tends to increase the noise level in the data. Iterative reconstruction methods can model scatter physics in the projector/backprojector and have been shown to provide more accurate reconstructions than subtracting/adding methods. See, for example: C. E. Floyd, et al., “Maximum Likelihood Reconstruction for SPECT with Monte Carlo Modeling: Asympt
Bai Chuanyong
Gullberg Grant T.
Zeng Gengsheng Lawrence
Boudreau Leo
Fay Sharpe Fagan Minnich & McKee LLP
Tabatabai Abolfazl
The University of Utah
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