Abstract: The present invention relates to a method and a cone beam computed tomography apparatus for reducing artefacts in an image acquired with the cone beam computed tomography apparatus using a second pass artefact reduction method. Projection data of an object are acquired, wherein the projection data comprises a first subset of data to be used for reconstruction of a first image, and a second subset of data comprising projection data not to be used for the construction of the first image, wherein the second subset of data comprises projection data not comprised in the first subset of data. A first and a second image are reconstructed using the first and the second subset of data, respectively. A second pass artefact reduction method is performed using the second image as input image of the second pass artefact reduction method, thereby reducing artefacts in the first image.

Abstract: A method and system are provided for reconstructing a motion-compensated nuclear image of a subject, as well as an arrangement for method. The reconstruction method comprises receiving nuclear image data the acquiring a nuclear image, and a computer program for carrying out the for multiple motion states, reconstructing the data into an image for each motion state, and calculating a deformation vector field for each state for mapping the image onto a reference motion state. Calculating the deformation vector field comprises providing an initial vector field, defining at least one rigid region of the subject, incorporating that rigid region into the initial vector field, and calculating the deformation vector field with the incorporated rigid region. The method further comprises mapping the reconstructed image of each motion state onto the reference state using the deformation vector fields; and combining the mapped images into a motion-compensated nuclear image.

Abstract: Motion compensated reconstruction is currently not well-suited for reconstructing the valve, the valve leaflets and the neighboring vascular anatomy of the heart. Blurring of the valve and the valve leaflets occurs. This may lead to wrong diagnosis. A new approach for motion compensated reconstruction of the valve and the related anatomy is presented in which an edge-enhancing step is performed to suppress blurring.

Abstract: A medical imaging system (200) includes a masking unit (234), an image registration unit (238), a motion estimator (240) and a motion compensating reconstructor (244). The masking unit constructs a mask for each reconstructed volumetric phase image of a plurality of reconstructed volumetric phase images that masks portions of a corresponding image external to an anatomical model fitted to a segmented at least one anatomical structure, 5 wherein the plurality of reconstructed volumetric phase images include a target phase and a plurality of temporal neighboring phases reconstructed from projection data. The image registration unit registers the masked reconstructed volumetric phase images. The motion estimator estimates motion between the target phase and the plurality of temporal neighboring phases according to the model based on the registered masked reconstructed 10 volumetric phase images.

Abstract: In a method and system for reconstructing computed tomography image data in which CT image data is de-noised. Then simulated noise is added, followed by another de-noising step to estimate the bias. Then, the estimated bias information is used to correct the original de-noised image data to arrive at second pass image data.

Abstract: An imaging method includes obtaining projection data for a helical scan of a subject. The method further includes reconstructing, for a particular time and image slice location of interest, a first temporal motion state image at an earlier time on the detector array and offset from the central row in a first direction with projection data from a first to subset of detector rows, and reconstructing, for the particular time and image slice location, a second temporal motion state image at a later time on the detector array and offset from the central row in a second direction with projection data from a second different subset of detector rows. The method further includes estimating a distortion vector field between the first and second temporal motion state images, and constructing motion compensated volu-metric image data with a motion compensated reconstruction algorithm using the distortion vector field to compensate for arbitrary motion.

Abstract: In a method and system for reconstructing computed tomography image data in which CT image data is de-noised. Then simulated noise is added, followed by another de-noising step to estimate the bias. Then, the estimated bias information is used to correct the original de-noised image data to arrive at second pass image data.

Abstract: Motion compensated reconstruction is currently not well-suited for reconstructing the valve, the valve leaflets and the neighboring vascular anatomy of the heart. Blurring of the valve and the valve leaflets occurs. This may lead to wrong diagnosis. A new approach for motion compensated reconstruction of the valve and the related anatomy is presented in which an edge-enhancing step is performed to suppress blurring.

Abstract: A computed tomography imaging system (102) includes an X-ray radiation source (110) configured to emit X-ray radiation that traverses an examination region (108) and an X-ray radiation sensitive detector array (112) configured to detect X-ray radiation traversing the examination region and generate a view of line integrals. The imaging system further includes a subject support table top (118) configured to translate in the examination region for a scan based on at least one scan parameter. The imaging system further includes an operator console (122), which includes a processor (128) and computer readable storage medium (130) with a scan parameter adapter module (132). The processor is configured to execute instructions of the scan parameter adapter module, which causes the processor to determine a contrast agent concentration from the view of line integrals and adjust the at least one scan parameter based on the determined concentration.

Abstract: A system includes a single backprojector (120), which includes a single geometry calculator (204), at least one weight calculator (206), and a plurality of data interpolators (208). The single geometry calculator is configured to process scan parameters of a single computed tomography scan to generate geometry values only once for each voxel position in a volumetric image data matrix. The at least one weight calculator is configured to process the scan parameters of the single computed tomography scan and the geometry values to generate weight values for each voxel position in the volumetric image data matrix. Each of the plurality of data interpolators is configured to process, using the weight values and the same geometry values, a respective different type of projection data produced from the same single computed tomography scan to generate volumetric image data based on the volumetric image data matrix and corresponding to the respective different type of projection data.

Abstract: The invention relates to a registration apparatus (14) for registering images comprising a unit (11) for providing a first and a second image of an object, such that an image element of the first image at a respective position has been reconstructed by multiplying projection data values of rays traversing the image element with weights and by backprojecting the weighted projection data values, a unit (12) for providing a confidence map comprising for different positions in the first image confidence values being indicative of a likelihood that an image feature is caused by a structure of the object, the confidence value being calculated as a sum of a function, which depends on the respective weight, over the rays traversing the respective image element, and a unit (13) for determining a transformation for registering the first and second image to each other under consideration of the confidence map.

Abstract: The present invention relates to an image reconstruction system for statistically reconstructing images from transmission measurements. The image reconstruction system comprises an update equation providing unit for providing an update equation based on an iterative statistical model. The update equation comprises a data term and a regularization term. The invention proposes to not modify the regularization term, but rather the weights with which individual measurements contribute are modified on a per image voxel and per measurement basis. This is achieved by modifying the contributions of each measurement by including an additional weight on a per image voxel/per measurement basis. The additional weight for each measurement is determined by calculating the noise perpendicular to each measurement ray at each voxel position and a voxel and measurement dependent weight for each measurement, and integrated into the update equation's data term.

Abstract: The invention relates to an image generation apparatus (1) for generating an image of an object. A reconstruction unit (10) reconstructs the image based on provided measured projection values such that costs defined by a cost function are reduced, wherein the cost function depends on differences between calculated projection values, which have been determined by simulating a forward projection through the image, and the provided measured projection values, and wherein a degree of dependence of the cost function on a respective difference depends on the respective difference. This can allow for a consideration of a degree of disturbance of the measured projection values by motion and/or by an incomplete illumination of the object during the reconstruction process, which can lead to a reconstruction of an image having an improved image quality.

Abstract: A medical imaging system (200) includes a masking unit (234), an image registration unit (238), a motion estimator (240) and a motion compensating reconstructor (244). The masking unit constructs a mask for each reconstructed volumetric phase image of a plurality of reconstructed volumetric phase images that masks portions of a corresponding image external to an anatomical model fitted to a segmented at least one anatomical structure, 5 wherein the plurality of reconstructed volumetric phase images include a target phase and a plurality of temporal neighboring phases reconstructed from projection data. The image registration unit registers the masked reconstructed volumetric phase images. The motion estimator estimates motion between the target phase and the plurality of temporal neighboring phases according to the model based on the registered masked reconstructed 10 volumetric phase images.

Abstract: The present invention relates to an image reconstruction system for statistically reconstructing images from transmission measurements. The image reconstruction system comprises an update equation providing unit for providing an update equation based on an iterative statistical model. The update equation comprises a data term and a regularization term. The invention proposes to not modify the regularization term, but rather the weights with which individual measurements contribute are modified on a per image voxel and per measurement basis. This is achieved by modifying the contributions of each measurement by including an additional weight on a per image voxel/per measurement basis. The additional weight for each measurement is determined by calculating the noise perpendicular to each measurement ray at each voxel position and a voxel and measurement dependent weight for each measurement, and integrated into the update equation's data term.

Abstract: A method includes obtaining a set of energy dependent data generated from a spectral scan. The set of energy dependent data includes a sub-set of data corresponding to only contrast agent. The method further includes separating the sub-set of data from other data of the energy dependent data. The other data includes non-contrast agent data. The method further includes scaling the sub-set of data to change a concentration of the contrast agent in the sub-set of data from that of the sub-set of data. The method further includes visually presenting at least the scaled sub-set of data.

Abstract: The invention relates to a registration apparatus (14) for registering images comprising a unit (11) for providing a first and a second image of an object, such that an image element of the first image at a respective position has been reconstructed by multiplying projection data values of rays traversing the image element with weights and by backprojecting the weighted projection data values, a unit (12) for providing a confidence map comprising for different positions in the first image confidence values being indicative of a likelihood that an image feature is caused by a structure of the object, the confidence value being calculated as a sum of a function, which depends on the respective weight, over the rays traversing the respective image element, and a unit (13) for determining a transformation for registering the first and second image to each other under consideration of the confidence map.

Abstract: A method includes re-sampling current image data representing a reference motion state into a plurality of different groups, each group corresponding to a different motion state of moving tissue of interest, forward projecting each of the plurality of groups, generating a plurality of groups of forward projected data, each group of forward projected data corresponding to a group of the re-sampled current image data, determining update projection data based on a comparison between the forward projected data and the measured projection data, grouping the update projection data into a plurality of groups, each group corresponding to a different motion state of the moving tissue of interest, back projecting each of the plurality of groups, generating a plurality of groups of update image data, re-sampling each group of update image data to the reference motion state of the current image, and generating new current image data based on the current image data and the re-sampled update image data.

Abstract: Image processing methods and related apparatuses (SEG,UV). The apparatuses (SEG,UV) operate to utilize noise signal information in images (IM). According to one aspect, apparatus (SEG) uses the noise information (FX) to control a model based segmentation. According to a further aspect, apparatus (UV) operates, based on the noise information (FX), to visualize the uncertainty of image information that resides at edge portions of the or an image (IM).

Abstract: A method includes obtaining a set of energy dependent data generated from a spectral scan. The set of energy dependent data includes a sub-set of data corresponding to only contrast agent. The method further includes separating the sub-set of data from other data of the energy dependent data. The other data includes non-contrast agent data. The method further includes scaling the sub-set of data to change a concentration of the contrast agent in the sub-set of data from that of the sub-set of data. The method further includes visually presenting at least the scaled sub-set of data.