82 results about "Tomographic image reconstruction" patented technology

A system for optical imaging of a thick specimen that permits rapid acquisition of data necessary for tomographic reconstruction of the three-dimensional (3D) image. One method involves the scanning of the focal plane of an imaging system and integrating the range of focal planes onto a detector. The focal plane of an optical imaging system is scanned along the axis perpendicular to said plane through the thickness of a specimen during a single detector exposure. Secondly, methods for reducing light scatter when using illumination point sources are presented. Both approaches yield shadowgrams. This process is repeated from multiple perspectives, either in series using a single illumination / detection subsystem, or in parallel using several illumination / detection subsystems. A set of pseudo-projections is generated, which are input to a three dimensional tomographic image reconstruction algorithm.

A system and method for tomographic image reconstruction using truncated limited-angle projection data that allows exact interior reconstruction (interior tomography) of a region of interest (ROI) based on the linear attenuation coefficient distribution of a subregion within the ROI, thereby improving image quality while reducing radiation dosage. In addition, the method includes parallel interior tomography using multiple sources beamed at multiple angles through an ROI and that enables higher temporal resolution.

A system and method for tomographic image reconstruction using truncated projection data that allows exact interior reconstruction (interior tomography) of a region of interest (ROI) based on the known sparsity models of the ROI, thereby improving image quality while reducing radiation dosage. In addition, the method includes parallel interior tomography using multiple sources beamed at multiple angles through an ROI and that enables higher temporal resolution.

In accordance with an embodiment, a system includes a plurality of vehicles and a central node. The plurality of vehicles each have radar systems used to collect radar data about the target object. Each in the plurality of vehicles moves in a path to collect a portion of the radar data using a sampling map to coordinate collection of the radar data by the plurality of vehicles and communicates with every other vehicle to identify uncollected portions of the radar data. The central node is in communication with the plurality of vehicles, wherein the central node receives the radar data from the plurality of vehicles and creates a three dimensional image from the radar data received from the plurality of vehicles using a tomographic reconstruction process.

A cloud virtual machine control system and method for CT equipment, belonging to the field of medical technology. Including: a local server with medical image data acquisition module, medical image data synchronization service module, local verification network module and medical image data remote transmission module, and a cloud computing management platform module, medical image data processing module and remote monitoring network module cloud server. Collect the original medical image projection data of CT equipment, and perform dead point and offset correction processing; perform integrity verification on the processed medical image data; write the integrity-verified medical image data into the medical image data synchronization service module , and transmit it to the cloud server and the doctor’s local control terminal through the medical image data remote transmission module for the doctor’s staff to monitor the local data; the preprocessing, tomographic image reconstruction, postprocessing and three-dimensional reconstruction of the medical image data are carried out in the cloud server; Invention saves space and reduces costs.

A tomographic image reconstruction method produces either 2D or 3D images from fan beam or cone beam projection data by filtering the backprojection image of differentiated projection data. The reconstruction is mathematically exact if sufficient projection data is acquired. A cone beam embodiment and both a symmetric and asymmetric fan beam embodiment are described.

The invention provides a mammary gland tomographic image reconstruction method and a mammary gland tomographic image reconstruction device. The mammary gland tomographic image reconstruction method comprises the steps of: initializing mechanical coordinates of mammary gland tomographic equipment and image parameters of a projected image; preprocessing the projected image; carrying out filtered back-projection on the projected image after preprocessing to generate a mammary gland 3D tomographic reconstructed image; removing detector edge artifacts in the mammary gland 3D tomographic reconstructed image; removing mammary gland edge artifacts in the mammary gland 3D tomographic reconstructed image; and removing sawtooth artifacts in the mammary gland 3D tomographic reconstructed image. The mammary gland tomographic image reconstruction method and the mammary gland tomographic image reconstruction device can be adapt to the mammary gland tomographic equipment with multiple ray sources.

Methods and systems for reconstructing an image are provided. The method includes performing a tomographic image reconstruction using a joint estimation of at least one of a gain parameter and an offset parameter, and an estimation of the reconstructed image.

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.

Algorithms are disclosed that recombine acquired data so as to generate a substantially uniform and complete set of frequency data where frequency data might otherwise be incomplete. This process, or its equivalent, may be accomplished in a computationally efficient manner using filtering steps in one or both of the reconstruction space and / or the post-processing space.

The invention discloses a CT digital subtraction angiography (CT / DSA) imaging system and CT digital subtraction angiography (CT / DSA) imaging method. The CT / DSA imaging system is composed of an x-ray generator, an energy resolution photon counting detector, a CT image reconstruction unit, a digital image subtraction unit, an image storage, transmission and display unit, an examining bed, a machine frame and a controller, wherein an x-ray source generates continuous energy spectrum x rays for fast scanning the human body; the energy resolution photon counting detector is used for detecting the x photons penetrating through the human body and judging and counting the energy of the x photons; the CT image reconstruction unit is used for collecting signals output by the energy resolution photon counting detector, so that two groups of transmission projection data of a high-energy area and a low-energy area are formed, and the projection data of the high-energy area and the projection data of the low-energy area are subjected to tomography image reconstruction by adopting an analytical reconstruction algorithm or a statistical reconstruction algorithm; the digital image subtraction unit is used for applying different weights to the tomography reconstruction images of the high-energy area and the low-energy area of each same scanning position and carrying out subtraction calculation, and thus the CT digital subtraction angiography image is obtained.

Tomography by emission of positrons (pet) system dedicated to examinations of human body parts such as the breast, axilla, head, neck, liver, heart, lungs, prostate region and other body extremities which is composed of at least two detecting plates (detector heads) with dimensions that are optimized for the breast, axilla region, brain and prostrate region or other extremities; motorized mechanical means to allow the movement of the plates under manual or computer control, making it possible to collect data in several orientations as needed for tomographic image reconstruction; an electronics system composed by a front-end electronics system, located physically on the detector heads, and a trigger and data acquisition system located off-detector in an electronic crate; a data acquisition and control software; and an image reconstruction and analysis software that allows reconstructing, visualizing and analyzing the data produced during the examination.

In a tomographical image reconstruction method and apparatus to generate an image of an examination subject from a number of digital projection data acquired at different projection angles, a first analytical filter kernel (formed by a first analytical function) is determined for a filtered back projection in the spatial frequency range, this first analytical filter kernel approximating, at least in a range of the spatial frequency, a discrete filter kernel iteratively determined for a model. Back projection is implemented with a second analytical filter kernel calculated from the analytical filter kernel and formed by a second analytical function.

A method of performing a computed tomographic image reconstruction is provided. The method provides for performing a short scan of an imaging object to acquire a short scan data, performing a plurality of image reconstructions based on the short scan data wherein the plurality of image reconstructions result in a corresponding plurality of image volumes wherein the image reconstructions use different view weighting functions, filtering the plurality of image volumes such that when the volumes are added together, the frequency domain data is substantially uniformly weighted. Further, the method provides for combining the plurality of image volumes together to produce a final image volume.