2784results about "Reconstruction from projection" patented technology

An apparatus and method for reconstructing image data for a region are described. A radiation source and multiple one-dimensional linear or two-dimensional planar area detector arrays located on opposed sides of a region angled generally along a circle centered at the radiation source are used to generate scan data for the region from a plurality of diverging radiation beams, i.e., a fan beam or cone beam. Individual pixels on the discreet detector arrays from the scan data for the region are reprojected onto a new single virtual detector array along a continuous equiangular arc or cylinder or equilinear line or plane prior to filtering and backprojecting to reconstruct the image data.

Tomography limitations in vivo due to incomplete, inconsistent and intricate measurements require solution of inverse problems. The new strategies disclosed in this application are capable of providing faster data acquisition, higher image quality, lower radiation dose, greater flexibility, and lower system cost. Such benefits can be used to advance research in cardiovascular diseases, regenerative medicine, inflammation, and nanotechnology. The present invention relates to the field of medical imaging. More particularly, embodiments of the invention relate to methods, systems, and devices for imaging, including tomography-based and MRI-based applications. For example, included in embodiments of the invention are compressive sampling based tomosynthesis methods, which have great potential to reduce the overall x-ray radiation dose for a patient. To name a few, compressive sensing based carbon nano-tube based interior tomosynthesis systems, tomography-based dynamic cardiac elastography systems, cardiac elastodynamic biomarkers from interior MR imaging, exact and stable interior ROI reconstructions for radial MRI, and interior reconstruction based ultrafast tomography systems are provided.

A system and method are disclosed for reconstructing contrast-enhanced CT images that are substantially free of beam-hardening artifacts. An imaging system includes a radiation source configured to project radiation toward an object to be scanned and an energy discriminating detector assembly having a plurality of detector elements and configured to detect radiation emitted by the radiation source and attenuated by the object to be scanned. The imaging system also includes computer programmed to count a number of photons detected by each detector element and associate an energy value to each counted photon and determine a material composition of a CT view from the number of photons counted and the energy value associated with each counted photon. The computer is also programmed to apply a weighting to the CT view based on the material composition of the CT view and reconstruct an image with differential weighting based on the weighting of the CT view.

The present invention relates to methods and systems for conducting three-dimensional image analysis and diagnosis and possible treatment relating thereto. The invention includes methods of handling signals containing information (data) relating to three-dimensional representation of objects scanned by a scanning medium. The invention also includes methods of making and analyzing volumetric measurements and changes in volumetric measurements which can be used for the purpose of diagnosis and treatment.

Registration correction for optical tomographic imaging in three dimensions. An object of interest is illuminated to produce an image. A lateral offset correction value is determined for the image. An axial offset correction value is determined for the image. The lateral offset correction value and the axial offset correction value are applied to the image to produce a corrected file image.

A system and method for estimating vascular flow using CT imaging include a computer readable storage medium having stored thereon a computer program comprising instructions, which, when executed by a computer, cause the computer to acquire a first set of data comprising anatomical information of an imaging subject, the anatomical information comprises information of at least one vessel. The instructions further cause the computer to process the anatomical information to generate an image volume comprising the at least one vessel, generate hemodynamic information based on the image volume, and acquire a second set of data of the imaging subject. The computer is also caused to generate an image comprising the hemodynamic information in combination with a visualization based on the second set of data.

A technique is provided for geometrical analysis and calibration of a volumetric imaging system. The technique includes computing a projection error between estimated locations of a set of markers of a phantom based on a estimated imaging geometry and observed locations of the respective markers for at least one projection image, decomposing the computed projection error into one or more error components corresponding to respective geometric parameters of the imaging geometry, and updating at least one parameter of the estimated imaging geometry based on the one or more error components.

The invention provides a method and apparatus for making reduced numbers of measurements compared to current practice and still give acceptable quality reconstructions of the object of interest. In one embodiment, a digital signal or image is approximated using significantly fewer measurements than with traditional measurement schemes. A component x of the signal or image can be represented as a vector with m entries; traditional approaches would make m measurements to determine the m entries. The disclosed technique makes measurements y comprising a vector with only n entries, where n is less than m. From these n measurements, the disclosed invention delivers an approximate reconstruction of the m-vector x. In another embodiment, special measurement matrices called CS-matrices are designed for use in connection with the embodiment described above. Such measurement matrices are designed for use in settings where sensors can allow measurements y which can be represented as y=Ax+z, with y the measured m-vector, x the desired n-vector and z an m-vector representing noise. Here, A is an n by m matrix, i.e. an array with fewer rows than columns. A technique is disclosed to design matrices A which support delivery of an approximate reconstruction of the m-vector x, described above. Another embodiment of the invention discloses approximate reconstruction of the vector x from the reduced-dimensionality measurement y within the context of the embodiment described above. Given the measurements y, and the CS matrix A, the invention delivers an approximate reconstruction x^# of the desired signal x. This embodiment is driven by the goal of promoting the approximate sparsity of x^#.

The invention relates to a system and a method for the generation of 3D images of a moving joint (1). A rotational X-ray device (10) generates projections of said joint from different directions while the simultaneous periodic movement of the joint (1) is recorded by a monitoring device (20). The generated X-ray projections are then classified according to the phase of joint movement to which they belong, and 3D images are reconstructed from X-ray projections of each class. Thus a 3D movie of the joint movement can be produced and shown on a monitor. The monitoring device (20) may particularly be realized by an apparatus that allows the forced movement of the joint (1) in synchronization with the generation of X-ray projections.

Described are systems, media, and methods for applying deep convolutional neural networks to medical images to generate a real-time or near real-time diagnosis.

The present invention relates to methods and systems for conducting three-dimensional image analysis and diagnosis and possible treatment relating thereto. The invention includes methods of handling signals containing information (data) relating to three-dimensional representation of objects scanned by a scanning medium. The invention also includes methods of making and analyzing volumetric measurements and changes in volumetric measurements which can be used for the purpose of diagnosis and treatment.

An X-ray CT apparatus includes a plurality of X-ray irradiation sources and a plurality of X-ray detection units. Timing of irradiation of X-ray is shifted by each X-ray irradiation source, the detection unit separately obtains projection data and scatter correction data. In a scatter correction unit, scatter correction is performed based on the projection data and the scatter correction data.

A method for reconstructing a high quality image from undersampled image data is provided. The image reconstruction method is applicable to a number of different imaging modalities. Specifically, the present invention provides an image reconstruction method that incorporates an appropriate prior image into the image reconstruction process. Thus, one aspect of the present invention is to provide an image reconstruction method that requires less number of data samples to reconstruct an accurate reconstruction of a desired image than previous methods, such as, compressed sensing. Another aspect of the invention is to provide an image reconstruction method that produces a time series of desired images indicative of a higher temporal resolution than is ordinarily achievable with the imaging system. For example, cardiac phase images can be produced with high temporal resolution (e.g., 20 milliseconds) using a CT imaging system with a slow gantry rotation speed.

The invention provides improvements in reconstructive imaging of the type in which a volume is reconstructed from a series of measured projection images (or other two-dimensional representations) generated by projection of a point x-ray source (or other radiation source), positioned at a distinct focus, through the volume to a plane at which the respective projection image is acquired (“detector plane”). In one aspect, the improvements are with respect to back-projecting a two-dimensional representation lying in the detector plane (representing, for example, a difference between an originally-acquired measured projection image and a subsequently-generated estimate thereof) to generate three-dimensional representation (which can be used, for example, to update an estimate of the volume). According to this aspect, for each of one or more slices of the 3D representation parallel to the projection plane and for each distinct focus at which a projection is generated, the following steps are performed in connection with the back-projection: (i) warping the first 2D representation to generate a second 2D representation by applying to the first 2D representation a selected linear mapping, where that selected linear mapping would map, in order to match dimensions of the respective slice within the 3D representation, a region defined by projection, at the respective focus, of comers of that slice onto the detector plane, and (ii) incrementing values of each of one or more voxels of the respective slice by an amount that is a function of a value of a correspondingly indexed pixel of the second 2D representation. A related aspect provides improvements with respect to forward-projecting, as well as in iterative (and non-iterative) methodologies that incorporate both back-projection and forward-projection.

An image processing apparatus is provided for processing a plurality of sets of projection data acquired by radiating an X-ray onto an object in a multitude of directions. The apparatus has a correcting unit and a reconstructing unit. The correcting unit corrects the projection data with regard to beam hardening of the projection data. The beam hardening is caused due to a contrast agent injected into the object. For example, the correcting unit includes a correction table defining a correcting value to a change in densities of a region in which the contrast agent is present and corrects the projection data on the basis of the correcting value obtained from the correction table. The reconstructing unit reconstructs the corrected projection data into an image of the object. Thus, artifacts due to beam hardening resultant from use of the contrast agent can be avoided.

A transmission wave field imaging method, comprising the transmission of an incident wave field into an object, the incident wave field propagating into the object and, at least, partially scattering. Also includes the measuring of a wave field transmitted, at least in part, through an object to obtain a measured wave field, the measured wave field based, in part, on the incident wave field and the object. Additionally, the processing of the measured wave field utilizing a recursive reconstruction algorithm to generate an image data set representing at least one image of the object.

The present invention provides a method for embedding particles in a solid structure including the steps of extruding a slurry of particles and a polymeric solution into a linear polymer medium having particles embedded into a polymer portion; and curing the polymer portion of the linear polymer medium.

Disclosed is a method and apparatus for generating a two dimensional (2D) image of a structure (e.g., an organ) that has at least one pixel corresponding to at least one voxel of a three dimensional (3D) image of the structure. First, the surface of the structure in the 3D image is modeled by a geometrical volume such as an ellipsoid. Next, normal maximum intensity projection (MIP) rays are cast (i.e., projected) for voxels of the geometrical volume. The 2D image is then generated using the rays. The 2D image has at least one pixel that corresponds to at least one voxel of the 3D image.

A system to illustrate image data of an imaged subjected is provided. The system comprises an imaging system, an input device, an output device, and a controller in communication with the imaging system, the input device, and the output device. The controller includes a processor to perform program instructions representative of the steps of generating a three-dimensional reconstructed volume from the plurality of two-dimensional, radiography images, navigating through the three-dimensional reconstructed volume, the navigating step including receiving an instruction from an input device that identifies a location of a portion of the three-dimensional reconstructed volume, calculating and generating a two-dimensional display of the portion of the three-dimensional reconstructed volume identified in the navigation step, and reporting the additional view or at least one parameter to calculate and generate the additional view.

A cardiac functional analysis system reconstructs a 3D anatomical image volume using image frames acquired at predetermined cardiac phases over multiple cardiac cycles in response to a trigger derived from hemodynamic signals. A medical imaging system generates 3D anatomical imaging volume datasets from acquired 2D anatomical images. The system includes an image acquisition device for acquiring 2D anatomical images of a portion of patient anatomy in selectable angularly variable imaging planes in response to a synchronization signal derived from a patient blood flow related parameter. A synchronization processor provides the synchronization signal derived from the patient blood flow related parameter. An image processor processes 2D images acquired by the image acquisition device of the portion of patient anatomy in multiple different imaging planes having relative angular separation, to provide a 3D image reconstruction of the portion of patient anatomy.

The present invention provides methods of using current but incomplete data to prepare an approximated complete image of a patient potentially undergoing radiation therapy. A complete image of the patient is fused or aligned with a limited patient image using image registration techniques. The aligned image is converted to sinogram data. This sinogram data is compared to sinogram data corresponding to the limited patient image to determine what data exists beyond the scope of the limited sinogram. Any additional data is added to the limited data sinogram to obtain a complete sinogram. This complete sinogram is then reconstructed into an image that approximates the complete image that would have been taken at the time the limited image was obtained.

The invention provides in one aspect methods and apparatus for use with C-arm and other CT systems, e.g., with non-rigid geometries. In such systems, by way of example, calibration can be performed to determine the exact position of the x-ray source and the exact orientation of the detector where each projection measurement is made. Next, a weighting coefficient can be determined for the voxels in each plane of a reconstruction volume at every possible projection. Finally, the order in which to process the voxels during image reconstruction can be determined. Following an actual CT scan procedure in which scans are obtained of a volume to be constructed, a system according to these and related aspects of the invention can use an optimal, pre-calculated processing method, while utilizing offsets and weighting coefficients determined during calibration, for performing backprojection image reconstruction.

Tomographic/tomosynthetic image reconstruction systems and methods in the framework of machine learning, such as deep learning, are provided. A machine learning algorithm can be used to obtain an improved tomographic image from raw data, processed data, or a preliminarily reconstructed intermediate image for biomedical imaging or any other imaging purpose. In certain cases, a single, conventional, non-deep-learning algorithm can be used on raw imaging data to obtain an initial image, and then a deep learning algorithm can be used on the initial image to obtain a final reconstructed image. All machine learning methods and systems for tomographic image reconstruction are covered, except for use of a single shallow network (three layers or less) for image reconstruction.

A magnetic resonance imaging (MRI) system, comprising: a magnetics system comprising: a B₀ magnet configured to provide a B₀ field for the MRI system; gradient coils configured to provide gradient fields for the MRI system; and at least one RF coil configured to detect magnetic resonance (MR) signals; and a controller configured to: control the magnetics system to acquire MR spatial frequency data using non-Cartesian sampling; and generate an MR image from the acquired MR spatial frequency data using a neural network model comprising one or more neural network blocks including a first neural network block, wherein the first neural network block is configured to perform data consistency processing using a non-uniform Fourier transformation.

A method and apparatus include acquisition of a view dataset based on x-rays received by a detector corresponding to a energy level, reconstruction of an initial image using the view dataset, the initial image comprising a plurality of metal voxels at respective metal voxel locations, and generation of a metal mask corresponding to the plurality of metal voxels within the initial image. The method and apparatus also include forward projection of the metal mask onto the view dataset to identify metal dexels in the view dataset, performance of a weighted interpolation based on the identified metal dexels to generate a completed view dataset, reconstruction of a final image using the completed view dataset, the final image comprising a plurality of image voxels corresponding to the metal voxel locations, and replacement of a portion of the plurality of image voxels corresponding to the metal voxel locations with smoothed metal values.

A method for improving a resolution of an image is provided. The method includes reconstructing an image of an initial portion of an object at an initial resolution, and reconstructing an additional portion of the object at an additional resolution.

A general imaging scheme is proposed for applications of CBCT. The approach provides a superior CBCT image quality by effective scatter correction and noise reduction. Specifically, in its implementation of CBCT imaging for radiation therapy, the proposed approach achieves an accurate patient setup using a partially blocked CBCT with a significantly reduced radiation dose. The image quality improvement due to the proposed scatter correction and noise reduction also makes CBCT-based dose calculation a viable solution to adaptive treatment planning.

Two-dimensional or three-dimensional, time-resolved CT frame images are acquired during a dynamic study of a subject. A composite image is produced and this is used to reconstruct each CT frame image by weighting the backprojection of each projection view acquired for that image frame by the corresponding value in the composite image. This weighted backprojection enables artifact-free image frames to be produced with far fewer projection views of the subject. The composite image may be reconstructed from views acquired separately, or it may be produced by combining views acquired during the course of the dynamic study.

Computerized interpretation of medical images for quantitative analysis of multi-modality breast images including analysis of FFDM, 2D/3D ultrasound, MRI, or other breast imaging methods. Real-time characterization of tumors and background tissue, and calculation of image-based biomarkers is provided for breast cancer detection, diagnosis, prognosis, risk assessment, and therapy response. Analysis includes lesion segmentation, and extraction of relevant characteristics (textural/morphological/kinetic features) from lesion-based or voxel-based analyses. Combinations of characteristics in several classification tasks using artificial intelligence is provided. Output in terms of 1D, 2D or 3D distributions in which an unknown case is identified relative to calculations on known or unlabeled cases, which can go through a dimension-reduction technique. Output to 3D shows relationships of the unknown case to a cloud of known or unlabeled cases, in which the cloud demonstrates the structure of the population of patients with and without the disease.

The present discussion relates to the use of deep learning techniques to accelerate iterative reconstruction of images, such as CT, PET, and MR images. The present approach utilizes deep learning techniques so as to provide a better initialization to one or more steps of the numerical iterative reconstruction algorithm by learning a trajectory of convergence from estimates at different convergence status so that it can reach the maximum or minimum of a cost function faster.