Abstract: A method and apparatus is provided to reconstruct a computed tomography image from projection data using windowed filtered back-projection (FBP) and using regularization constraints that can be quadratic or non-quadratic. The method emulates multiple Landweber iterations using a single windowed FBP operation and then iterates between imposing regularization constraints and a single windowed FBP operation. This windowed FBP operation is only performed once. The regularization constraints can be imposed using edge-preserving denoising methods, including, e.g., a Huber filter, a median filter, a bilateral filter, a guided filter, a non-local means filter, a total-variation minimization regularizer, other known regularizer, or an anisotropic diffusion filter. The entire procedure contains no forward projection and contains only one back-projection.

Abstract: A method and apparatus is provided to reconstruct a computed tomography image from projection data using windowed filtered back-projection (FBP) and using regularization constraints that can be quadratic or non-quadratic. The method emulates multiple Landweber iterations using a single windowed FBP operation and then iterates between imposing regularization constraints and a single windowed FBP operation. This windowed FBP operation is only performed once. The regularization constraints can be imposed using edge-preserving denoising methods, including, e.g., a Huber filter, a median filter, a bilateral filter, a guided filter, a non-local means filter, a total-variation minimization regularizer, other known regularizer, or an anisotropic diffusion filter. The entire procedure contains no forward projection and contains only one back-projection.

Abstract: Systems and methods are provided which utilize a fast, efficient filtered backprojection algorithm that can provide noise suppression advantages of an iterative MAP reconstruction algorithm. In some embodiments novel filtered backprojection systems are able to provide an image which emulates an image from an iterative algorithm corresponding to a selected iteration by utilizing control parameters which shape the filter accordingly during the reconstruction process. For example, if a user desires an image which would correspond to the one-hundredth iteration of an iterative algorithm, embodiments can provide a similar quality image using minimal calculation steps. Further, embodiments may provide the resolution quality of such an iteration while also allowing for better shift-invariant performance than an iterative method.

Abstract: Systems and methods are provided which utilize a fast, efficient filtered backprojection algorithm that can provide noise suppression advantages of an iterative MAP reconstruction algorithm. In some embodiments novel filtered backprojection systems are able to provide an image which emulates an image from an iterative algorithm corresponding to a selected iteration by utilizing control parameters which shape the filter accordingly during the reconstruction process. For example, if a user desires an image which would correspond to the one-hundredth iteration of an iterative algorithm, embodiments can provide a similar quality image using minimal calculation steps. Further, embodiments may provide the resolution quality of such an iteration while also allowing for better shift-invariant performance than an iterative method.

Abstract: The present invention provides methods, systems and machine readable medium including machine readable code for deblurring data corrupted by shift variant blurring. A first version of data having shift variant blurring characterized by a first shift variant point spread function is provided. A target shift invariant point spread function is selected. A second shift variant point spread function is derived wherein a combination of the first and second shift variant point spread functions generates the target shift invariant point spread function. The second shift variant point spread function is applied to the first version of the data thereby generating a second version of the data having shift invariant blurring characterized by the target shift invariant point spread function. A linear shift invariant filter is applied to the second version of the data thereby generating a deblurred version of the data.

Abstract: A collimator and related methods are shown and described. The collimator can be a multi-divergent-beam collimator having a plurality of inverted, ordered sections of a cone-beam collimator reassembled in a substantially reversed order relative to the ordering of the cone-beam collimator.

Abstract: The present invention provides methods, systems and machine readable medium including machine readable code for deblurring data corrupted by shift variant blurring. A first version of data having shift variant blurring characterized by a first shift variant point spread function is provided. A target shift invariant point spread function is selected. A second shift variant point spread function is derived wherein a combination of the first and second shift variant point spread functions generates the target shift invariant point spread function. The second shift variant point spread function is applied to the first version of the data thereby generating a second version of the data having shift invariant blurring characterized by the target shift invariant point spread function. A linear shift invariant filter is applied to the second version of the data thereby generating a deblurred version of the data.

Abstract: The present invention provides methods, systems and machine readable medium including machine readable code for deblurring data corrupted by shift variant blurring. A first version of data having shift variant blurring characterized by a first shift variant point spread function is provided. A target shift invariant point spread function is selected. A second shift variant point spread function is derived wherein a combination of the first and second shift variant point spread functions generates the target shift invariant point spread function. The second shift variant point spread function is applied to the first version of the data thereby generating a second version of the data having shift invariant blurring characterized by the target shift invariant point spread function. A linear shift invariant filter is applied to the second version of the data thereby generating a deblurred version of the data.

Abstract: A collimator and related methods are shown and described. The collimator can be a multi-divergent-beam collimator having a plurality of inverted, ordered sections of a cone-beam collimator reassembled in a substantially reversed order relative to the ordering of the cone-beam collimator.

Abstract: The present invention provides methods, systems and machine readable medium including machine readable code for deblurring data corrupted by shift variant blurring. A first version of data having shift variant blurring characterized by a first shift variant point spread function is provided. A target shift invariant point spread function is selected. A second shift variant point spread function is derived wherein a combination of the first and second shift variant point spread functions generates the target shift invariant point spread function. The second shift variant point spread function is applied to the first version of the data thereby generating a second version of the data having shift invariant blurring characterized by the target shift invariant point spread function. A linear shift invariant filter is applied to the second version of the data thereby generating a deblurred version of the data.

Abstract: A skew slit collimator for a gamma ray imaging device and a method of configuring the skew slit collimator for a gamma ray imaging device is disclosed. The gamma ray imaging device includes a detector having a generally planar detector surface. The detector surface is operable to be positioned adjacent a subject imaging region. The skew slit collimator includes a first collimator blade having a first slit and a second collimator blade having a second slit. The first collimator blade is disposed in front of and generally parallel to the detector surface. The second collimator blade is disposed between the first collimator blade and the detector surface. The second collimator is generally parallel to and spaced apart from the first collimator blade. The second collimator blade is oriented with respect to the first collimator blade such that the lengthwise orientation of the second slit is generally orthogonal to a lengthwise orientation of the first slit.

Abstract: A rotating laminar emission camera includes a detector (22) which detects radiation. The detector (22) has a radiation receiving side (23) that faces an object (e.g., a patient 200) being studied. The detector (22) includes an array of detection elements (106), the array extending in a first direction across the radiation receiving side (23) of the detector (22). The detection elements (106) each individually detect radiation incident thereon. A collimator (100) constructed of a radiation attenuative material is arranged on the radiation receiving side (23) of the detector (22). The collimator (100) experiences relative rotation about an axis (109) substantially normal to the radiation receiving side (23) of the detector (22). The relative rotation is relative to the object being studied. The collimator (100) includes a plurality of spaced apart slats (102) each extending in a second direction across the radiation receiving side (23) of the detector (22).

Abstract: &ggr;-ray emissions (14) are detected by a rotating, one-dimensional detector array (18). Slats of a convergent or divergent collimator (16) are mounted between detector elements. The slats are canted by an angle &agr; from focusing on a focal spot (40) on a perpendicular bisector to the detector array. As a detector head (30) revolves around a longitudinal axis (36) of the subject, the head is canted (FIG. 5) to generate angularly offset data sets. Data sets with the detector array rotated to 180° opposite orientations are processed (62) to generate a first derivative data set. Parallel lines or planes (64) of the canted data sets are processed (68) to generate a second derivative data set which is backprojected (70) in accordance with the Radon transform into a three-dimensional image representation.

Abstract: A rotating laminar emission camera is provided. The camera includes a detector having a side which detects radiation facing an object being studied. The detector rotates about a central axis (109) perpendicular to the side of the detector facing the object. A collimator (100) constructed of a radiation attenuative material is arranged on the side of the detector facing the object. The collimator (100) including a plurality of spaced apart slats (102) which are tilted at an angle a greater than zero with respect to the axis (109).

Abstract: A subject (10) is disposed adjacent a linear detector array (18) of a nuclear camera. The subject (10) is injected with a radioactive isotope (14) and y-ray emissions indicative of nuclear decay are detected at the detector array (18) as the detector array rotates about an axis of rotation to collect data over a circular field of view. Detectors farther from the axis rotation are sampled at a higher sampling rate such that the are sampled after a generally constant arc of rotation to correct for angular aliasing. The detector array (18) rotates about the axis of rotation in a 1/sin &THgr; pattern with angular offset of the detector array from a longitudinal axis of the subject. This corrects for otherwise uneven sampling. A reconstruction processor (84) reconstructs the identifications of the y-ray receiving detectors, or other indicators of event detection location, and the digital peak values to generate a spherical image representation.

Abstract: A rotating laminar emission camera includes a detector (22) which detects radiation. The detector (22) has a radiation receiving side (23) that faces an object (e.g., a patient 200) being studied. The detector (22) includes an array of detection elements (106), the array extending in a first direction across the radiation receiving side (23) of the detector (22). The detection elements (106) each individually detect radiation incident thereon. A collimator (100) constructed of a radiation attenuative material is arranged on the radiation receiving side (23) of the detector (22). The collimator (100) experiences relative rotation about an axis (109) substantially normal to the radiation receiving side (23) of the detector (22). The relative rotation is relative to the object being studied. The collimator (100) includes a plurality of spaced apart slats (102) each extending in a second direction across the radiation receiving side (23) of the detector (22).

Abstract: A method of constructing a non-uniform attenuation map (460) of a subject for use in image reconstruction of SPECT data is provided. It includes collecting a population of a priori transmission images and storing them in an a priori image memory (400). The transmission images not of the subject. Next, a cross-correlation matrix (410) is generated from the population of transmission images. The eigenvectors (420) of the cross-correlation matrix (410) are calculated. A set of orthonormal basis vectors (430) is generated from the eigenvectors (420). A linear combination of the basis vectors (420) is constructed (440), and coefficients for the basis vectors are determined (450) such that the linear combination thereof defines the non-uniform attenuation map (460).

Abstract: A method of modeling 3D first-order scatter, non-uniform attenuation, and 3D system geometric point response in an ML-EM algorithm to reconstruction SPECT data is provided. It includes performing an initial slice-to-slice blurring operation (112) on a volume of estimated emission source data. The volume of estimated emission source data is represented by a 3D array of voxels. A voxel-by-voxel multiplying (114) of the results from the initial slice-to-slice blurring operation (112) by a volume of attenuation coefficients yields a volume of effective scatter source data (116). The volume of effective scatter source data (116) is voxel-by-voxel added (118) to the volume of estimated emission source data to produce a volume of combined estimated emission and scatter source data. Finally, a secondary slice-to-slice blurring operation (120) is performed on the volume of combined estimated emission and scatter source data.

Abstract: A diagnostic imaging system includes a Compton camera (14) disposed on a gantry (16). The camera (14) includes linear detectors (30a, 30b) for detecting radiation emanating from a subject to be imaged. A data processor (32) collects and processes radiation data in accordance with the detected radiation. Position and energy resolving circuitry (34) determines positions and energy deposited by photons striking the detectors. A cone projection generator (40) generates cone projection data or cone integrals based on the collected data which determine a possible location of a gamma source of the detected radiation. A conversion processor (41) converts the cone projection data into plane projection data. The conversion processor (41) includes a line integral processor (42) which determines line integrals representing the cone projection data and applies a spherical harmonic expansion to the line integrals.

Abstract: A SPECT system includes a Compton camera (14) disposed on a gantry (16). The camera (14) includes linear detectors (30a, 30b) operating without mechanical collimation for detecting radiation emanating from a subject to be imaged. A data processor (22) collects and processes radiation data in accordance with the detected radiation. Position and energy resolving circuitry (24) determines positions and energy deposited by photons striking the detectors. A projection generator (34) generates divergent projections or V-projections based on the collected data which determine a possible location of a gamma source of the detected radiation. A conversion processor (36) converts the V-projections into parallel projection data such as a Radon transformation. A reconstruction processor (38) reconstructs an image representation of a region of interest from the subject from the parallel projection data using filtered back projection.