A method for movement compensation during CT reconstruction, comprises calculating slice images. The calculating slice images comprising: selecting an initial movement state; calculating a reference voxel position in relation to the initial movement state; calculating a column image position of a voxel; ascertaining a changed movement state of the voxel at the column image position; calculating a changed voxel position in relation to the changed movement state; calculating a changed image position of the voxel; and using an image value of the intermediate image at the changed image position for back projection to calculate the slice images.

In order to provide an arithmetic device, an X-ray CT apparatus, and an image reconstruction method, capable of reducing processing time while maintaining a noise reduction effect, in a successive approximation image reconstruction method (separable paraboloidal surrogate (SPS) method) of the related art, updated images are forward-projected, whenever images are repeatedly updated, a difference between forward projection data and original object projection data is back-projected so that a difference image is obtained, and a forward projection process and a back projection process are repeatedly performed, but, in the present invention, a forward projection process and a back projection process requiring calculation time are replaced with a process requiring a relatively small calculation amount, such as a difference between an updated image and a reference image, and, as a result, it is possible to considerably reduce a calculation amount in a successive approximation image reconstruction process and to reduce processing time.

A system includes obtaining de-noised reconstructed image data and edge improving a sub-set of the de-noised reconstructed image data corresponding to edges of structure represented in the de-noise reconstructed image data. A system (100) includes an edge detector (202) that detects an edge map of edge locations within de-noised reconstructed image data, a noise image data generator (204) that generates noise image data by subtracting the reconstructed image data by the de-noised reconstructed image data, a noisy edge image data generator (206) that generates noisy edge image data by multiplying the noise image data and the edge map, and an edge improver (208) that generates edge improved de-noised image data by adding the noisy edge image data and a product of a weight and the de-noised reconstructed image data.

In a method for producing 2-D recordings and 3-D recordings of a breast of a patient using an x-ray device that is operable in two recording modes and that has an x-ray radiation source and an x-ray radiation detector, the breast is placed between the x-ray radiation source and the x-ray radiation detector, and the 2-D recordings and the 3-D recordings are generated with the same breast placement. In order to keep the radiation exposure as low as possible in such a multi-mode x-ray device, all recordings are produced without the use of an anti-scatter grid, and a retroactive scattered radiation correction is implemented.

Methods and systems are provided for boosting the contrast levels in an image reconstructed from projection data acquired at a single energy. In one embodiment, a method comprises modifying projection data corresponding to a material based on an absorption behavior of the material at a selected energy, wherein the projection data is acquired at an energy higher than the selected energy. In this way, contrast levels may be enhanced in an image reconstructed from projection data acquired at a typical single energy as though the image were reconstructed from projection data acquired at a lower energy.

A computed tomography (CT) method and apparatus including a radiation source configured to produce radiation directed to an object space, and a plurality of detector elements configured to detect the radiation produced from the radiation source through the object space and generate projection data. A rotation mount is configured to rotate the radiation source around the object space. Processing circuitry is configured to cause the rotation mount to rotate the radiation source, and to receive the projection data. The projection data includes a plurality of projection data sets. The processing circuitry calculates a set of weights based on the projection data sets, calculates a set of pre-weights based on the weights, and minimizes a penalized weighted least-squares cost function to produce a reconstructed image. The cost function is a sum of a weighted least-squares term, weighted using the weights, and a penalty term weighted using the pre-weights.

For saliency mapping, a machine-learned classifier is used to classify input data. A perturbation encoder is trained and/or applied for saliency mapping of the machine-learned classifier. The training and/or application (testing) of the perturbation encoder uses less than all feature maps of the machine-learned classifier, such as selecting different feature maps of different hidden layers in a multiscale approach. The subset used is selected based on gradients from back-projection. The training of the perturbation encoder may be unsupervised, such as using an entropy score, or semi-supervised, such as using the entropy score and a difference of a perturbation mask from a ground truth segmentation.

A tomography apparatus that may reduce partial scan artifacts includes: a data acquirer configured to acquire tomography data when X-rays are emitted as a cone beam to an object while rotating by one cycle angular section that is less than one rotation; and an image reconstructor configured to reconstruct a tomography image by using corrected tomography data that is obtained by applying to the tomography data a weight that is set based on at least one of a view that is included in the one cycle angular section and a cone angle in the cone beam.

A method and system for image reconstruction are provided. A projection image of a projection object may be obtained. A processed projection image may be generated based on the projection image through one or more pre-process operations. A reconstructed image including an artifact may be reconstructed based on the processed projection image. The artifact may be a detector edge artifact, a projection object edge artifact, and a serrated artifact. The detector edge artifact, the projection object edge artifact, and the serrated artifact may be removed from the reconstructed image.

Various embodiments of the present technology generally relate to identification of tumor location. More specifically, some embodiments of the present technology relate automated tracking of fiducial marker clusters in x-ray images for the real-time identification of tumor location and guidance of radiation therapy beams. Some embodiments use processed CBCT projection images, an automated routine of reconstruction, forward-projection, tracking, and stabilization generated static templates of the marker cluster at arbitrary viewing angles. Breathing data can be incorporated into some embodiments, resulting in dynamic templates dependent on both viewing angle and breathing motion. In some embodiments, marker clusters can be tracked using normalized cross correlations between templates (either static or dynamic) and CBCT projection images.