The disclosure relates to system and method for CT image reconstruction. The method may include: obtaining scanning data, wherein the scanning data is generated by at least one detector via a plurality of axial scans; obtaining a scanning parameter wherein the scanning parameter include a detector size; obtaining a requested reconstruction parameter; determining a plurality of requested image locations based on the scanning parameter and the requested reconstruction parameter; determining an intermediate reconstruction parameter based on the requested reconstruction parameter; determining a plurality of intermediate image locations based on the plurality of requested image locations and the intermediate reconstruction parameter; determining a intermediate image volume based on the plurality of intermediate images and the scanning data; determining a final image volume based on the intermediate image volume and a filter; reconstructing an image of the subject based on the final image volume and the requested reconstruction parameters.

According to one embodiment, an information processing apparatus includes processing circuitry. The processing circuitry calculates a plurality of bases by performing a basis conversion on signal data. The processing circuitry selects one or more specific bases with contribution rates lower than a reference from among the bases. The processing circuitry executes data processing utilizing the specific bases.

The majority of image reconstruction algorithms are common to DT and CT, and require reconstruction volume allocation and are based on ray tracing techniques. Reconstructed three-dimensional images become available only after the entire volume is processed and the algorithm completes. The present invention performs reconstruction on a slice-by-slice basis, instead of waiting for completion of the algorithm by back-projecting each pixel in each attenuation image towards the emitter that generated that image, onto a selected reconstruction slice and determining a proportion of overlap with grid cells in the slice to obtain weighting factors in order to calculate an average back-projected intensity for each grid cell in the selected reconstruction slice.

A computer-implemented method and system of CT reconstruction can include receiving one or more CT projection images; performing smooth filtering on the one or more CT projection images to generate one or more smooth boundary filtered images; and back-projecting the one or more smooth boundary filtered images.

A medical image reconstruction method includes: obtaining real projection data collected by a medical imaging device; obtaining an inverse matrix corresponding to the medical imaging device that is physically stored in advance, in which the inverse matrix is obtained by performing an inverse operation based on a system matrix corresponding to the medical imaging device, and the system matrix indicating a geometrical relationship between projection rays of the medical imaging device at each view angle and of reconstructed image pixels; and determining a reconstructed image of the real projection data according to the real projection data and the inverse matrix. By storing a large inverse matrix of the system matrix, rapid image reconstruction may be achieved through the inverse matrix and the real projection data, reconstruction efficiency of a medical image may be improved, and wide application and development of iterative reconstruction technology in clinical practice may be promoted.

The present disclosure relates to a method and system for registering multi-modality images. The method may include: acquiring a first image relating to one or more reference objects; acquiring a second image relating to the one or more reference objects; determining a set of reference points based on the one or more reference objects; determining a set of mapping data corresponding to the set of reference points in the first image and the second image; and determining one or more registration parameters by comparing a plurality of back-projection errors generated in a plurality of iterations that are performed based on the set of mapping data.

Digital Tomosynthesis (DT) is a type of limited angle tomography providing the benefits of 3D imaging. Much like Computerized Tomography (CT), DT allows greater detection of 3D structures by viewing one slice at a time. In contrast to CT, the DT projection dataset is incomplete, which violates the tomographic sufficiency conditions and results in limited angle artefacts in the reconstructed images. The present invention provides a method of producing a tomogram in which reconstruction is performed along lines on the x-ray detector panel 20 defined by a point on the detector panel 20 closest to a point location of the x-ray emitter 10, to a location of a respective pixel on the perimeter of the x-ray detector panel 20. In this way, artefact reduction is achieved, particularly at higher cone beam angles, and at lower stand-off distances.

Accelerated filtered back projection for computed tomography image reconstruction. In an embodiment, a filtered back projection is performed on a sinogram. The back projection may comprise transitioning the sinogram to a linogram using linear interpolation, and performing an inverse Fast Hough Transform on the linogram to produce a reconstructed CT image. Filtering in the filtered back projection may use an infinite impulse response (IIR) filter.

The disclosure is directed to a method for generating a three dimensional (3D) volume including a treatment target including receiving a plurality of two dimensional (2D) input images of a patient, determining a metal artifact in each of the plurality of 2D input images, removing the metal artifacts from the plurality of 2D input images based on the determination of the metal artifact, and replacing metal artifacts with alternative pixel data to generate a plurality of filtered 2D images. A 3D volume is generated from the plurality of filtered 2D images. The plurality of 2D input images including a treatment target.

Various methods and systems are provided for spectral computed tomography (CT) imaging. In one embodiment, a method comprises performing a scan of a subject to acquire, with a detector array comprising a plurality of detector elements, projection data of the subject, generating corrected path-length estimates based on the projection data and one or more selected correction functions, and reconstructing at least one material density image based on the corrected path-length estimates. In this way, the fidelity of spectral information is improved, thereby increasing image quality for spectral computed tomography (CT) imaging systems, especially those configured with photon-counting detectors.