Abstract:
The present disclosure relates to the iterative reconstruction of projection data. In certain embodiments, the iterative reconstruction is a multi-stage iterative reconstruction in which different feature are selectively emphasized at different stages. Selective emphasis at different stages may be accomplished by differentially handling two or more decompositions of an input image at certain iterations and/or by differently processing certain features with respect to each stage.
Abstract:
Some embodiments are associated with generation of a volumetric image representing an imaged object associated with a patient. According to some embodiments, tomosynthesis projection data may be acquired. A computer processor may then automatically generate the volumetric image based on the acquired tomosynthesis projection data. Moreover, distances between voxels in the volumetric image may be spatially varied.
Abstract:
A method for imaging a target region in a subject is presented. The method includes selecting one or more tomographic angle sequences, acquiring one or more image sequences corresponding to the one or more tomographic angle sequences, where each image sequence has a corresponding tomographic angle sequence, deriving geometric information corresponding to one or more structures of interest in at least one of the image sequences, identifying visualization information, generating one or more displacement maps based on the geometric information, the visualization information, at least a subset of at least one of the one or more tomographic angle sequences, or combinations thereof, transforming at least a subset of images in the one or more image sequences based on corresponding displacement maps to create one or more transformed/stabilized image sequences, and visualizing on a display the one or more transformed/stabilized image sequences to provide a stabilized presentation of the target region.
Abstract:
An imaging system is provided. The imaging system includes an X-ray radiation source. The imaging system also includes a source controller coupled to the X-ray radiation source and configured to modulate an exposure pattern from the X-ray radiation source to enable a coded exposure sequence. The imaging system further includes a digital X-ray detector configured to acquire image data that includes at least one coded motion blur.
Abstract:
A method relates to the use of deep learning techniques, which may be implemented using trained neural networks (50), to estimate various types of missing projection or other unreconstructed data. Similarly, the method may also be employed to replace or correct corrupted or erroneous projection data as opposed to estimating missing projection data.
Abstract:
A method for imaging a target region in a subject is presented. The method includes selecting one or more tomographic angle sequences, acquiring one or more image sequences corresponding to the one or more tomographic angle sequences, where each image sequence has a corresponding tomographic angle sequence, deriving geometric information corresponding to one or more structures of interest in at least one of the image sequences, identifying visualization information, generating one or more displacement maps based on the geometric information, the visualization information, at least a subset of at least one of the one or more tomographic angle sequences, or combinations thereof, transforming at least a subset of images in the one or more image sequences based on corresponding displacement maps to create one or more transformed/stabilized image sequences, and visualizing on a display the one or more transformed/stabilized image sequences to provide a stabilized presentation of the target region.
Abstract:
The present disclosure relates various approaches by which mask and contrast projection data may be acquired using a continuous projection acquisition process, without an interruption in acquisition or resetting of the system between the acquisition of the mask projection data and the contrast projection data. In certain implementations, the approaches described herein may be employed with a single-plane or multi-plane tomosynthesis system.
Abstract:
The present disclosure relates to the identification and tracking of a navigational instrument (e.g., a needle) in three-dimensions, with substantially real-time image updates of the instrument and updates of the tissue at an equal or lower rate. In certain embodiments, the images are acquired using a C-arm tomosynthesis system configured to move the X-ray source and detector in respective planes above and below the patient.
Abstract:
A method includes, in a bi-plane interventional imaging system, moving a first C-arm supporting a first X-ray source and a first X-ray detector about first and second axes while obtaining a plurality of first X-ray attenuation data sets relating to a subject of interest; moving a second C-arm, positioned crosswise with respect to the first C-arm and supporting a second X-ray source and a second X-ray detector, about the first axis while obtaining a plurality of second X-ray attenuation data sets relating to the subject of interest; and synchronizing the movement of the first and second C-arms to avoid collision therebetween.
Abstract:
In accordance with the present disclosure, the present technique finds a diagnostic scan timing for a non-static object (e.g., a heart or other dynamic object undergoing motion) from raw scan data, as opposed to reconstructed image data. To find the scan timing, a monitoring scan of a patient's heart is performed. In the monitoring scan, the patient dose may be limited or minimized. As the projection data is acquired during such a monitoring scan, the projection data may be subjected to sinogram analysis in a concurrent or real-time manner to determine when to start (or trigger) the diagnostic scan.