摘要:
Bioluminescent imaging has proven to be a valuable tool for monitoring physiological and pathological activities at cellular and molecular levels in living small animals. Using biological techniques, target cells can be tagged with reporters which generate characteristic photons in a wide spectrum covering the infra-red range. Part of the diffused light can reach the body surface of a subject/specimen (e.g., a small animal), be separated into several spectral bands using optical means, and collected by a sensitive camera. Systems and methods are disclosed herein for multi-spectral bioluminescence tomography (MBLT), in which an image of an underlying 3D bioluminescent source distribution is synergistically reconstructed from spectrally resolved datasets externally measured. This MBLT process involves two or multiple imaging modalities that produce structural information of the object and optical properties of the object as well to enable and improve the quality of MBLT.
摘要:
A method for obtaining a distribution of a stiffness property in tissue includes applying a plurality of loadings to the tissue, obtaining a plurality of two-dimensional (2-D) imaging projections of the tissue from different directions, measuring a force resulting from one of the plurality of loadings, measuring from at least one of the plurality of 2-D imaging projections a displacement of the tissue in response to the force, obtaining an initial set of input parameters for an estimated stiffness property of the tissue, and solving iteratively for the stiffness property using a computer.
摘要:
The present invention relates to a method and system (CMCT system) for improving spatial resolution imaging of CT systems. The systems and method can achieve improved spatial resolution while using CT X-ray dosage levels comparable to those currently used in practice. The system and method can be used for micro-tomography and/or micortomosynthesis of a local region and/or volume of interest in a patient head or another body part.
摘要:
Provided herein are methods of reconstructing an image from projection data provided by a tomography scanner that is based on geometric optics comprising scanning an object in a cone-beam imaging geometry following a non-standard spiral path or a general piecewise smooth scanning path wherein projection data is generated and reconstructing an image according to a closed-form formula that is either in the filtered backprojection (FBP) or backprojection filtration (or backprojected filtration, BPF) formats. Also provided herein are associated systems and apparatuses for tomographic imaging.
摘要:
An image of an object is reconstructed in a three-dimensional coordinate system in an x-ray computed tomography system. A partial scan of the object is performed by rotating an x-ray beam having a cone beam geometry around a portion of the object or rotating the object in the cone-beam. The x-ray beam forms on a scanning trajectory through a plurality of projection lines from a plurality of successive focal point locations. The scanning trajectory may be substantially circular, helical, spiral, or spiral-like. The x-ray beam, attenuated by the object during the spiral scan, is detected to produce detector values. The detector values are integrated along straight lines on the detector plane to obtain intermediate data. Three-dimensional Radon values representing approximate plane integrals of the object are calculated from the intermediate data using a Grangeat relationship or a modified or extended version or the Grangeat relationship. The calculated and estimated Radon values are then reconstructed into an image volume according to the Radon inversion formula.
摘要:
A system for enhancing a low-dose (LD) computed tomography (CT) image is described. The system includes a modularized adaptive processing neural network (MAP-NN) apparatus and a MAP module. The MAP-NN apparatus is configured to receive a LDCT image as input. The MAP-NN apparatus includes a number, T, trained neural network (NN) modules coupled in series. Each trained NN module is configured to generate a respective test intermediate output image based, at least in part, on a respective received test input image. Each test intermediate output image corresponds to an incrementally denoised respective received test input image. The MAP module is configured to identify an optimum mapping depth, D, based, at least in part, on a selected test intermediate output image, the selected test intermediate output image selected by a domain expert. The mapping depth, D, is less than or equal to the number, T.
摘要:
In one embodiment, there is provided an apparatus for low-dimensional manifold constrained disentanglement for metal artifact reduction (MAR) in computed tomography (CT) images. The apparatus includes a patch set construction module, a manifold dimensionality module, and a training module. The patch set construction module is configured to construct a patch set based, at least in part on training data. The manifold dimensionality module is configured to determine a dimensionality of a manifold. The training module is configured to optimize a combination loss function comprising a network loss function and the manifold dimensionality. The optimizing the combination loss function includes optimizing at least one network parameter.
摘要:
A system for few-view computed tomography (CT) image reconstruction is described. The system includes a preprocessing module, a first generator network, and a discriminator network. The preprocessing module is configured to apply a ramp filter to an input sinogram to yield a filtered sinogram. The first generator network is configured to receive the filtered sinogram, to learn a filtered back-projection operation and to provide a first reconstructed image as output. The first reconstructed image corresponds to the input sinogram. The discriminator network is configured to determine whether a received image corresponds to the first reconstructed image or a corresponding ground truth image. The generator network and the discriminator network correspond to a Wasserstein generative adversarial network (WGAN). The WGAN is optimized using an objective function based, at least in part, on a Wasserstein distance and based, at least in part, on a gradient penalty.
摘要:
A system for enhancing a low-dose (LD) computed tomography (CT) image is described. The system includes a modularized adaptive processing neural network (MAP-NN) apparatus and a MAP module. The MAP-NN apparatus is configured to receive a LDCT image as input. The MAP-NN apparatus includes a number, T, trained neural network (NN) modules coupled in series. Each trained NN module is configured to generate a respective test intermediate output image based, at least in part, on a respective received test input image. Each test intermediate output image corresponds to an incrementally denoised respective received test input image. The MAP module is configured to identify an optimum mapping depth, D, based, at least in part, on a selected test intermediate output image, the selected test intermediate output image selected by a domain expert. The mapping depth, D, is less than or equal to the number, T.
摘要:
Dynamic bowties, imaging systems including a bowtie, and methods of imaging including such bowties or systems are provided. A bowtie can be a three-dimensional (3-D) dynamic bowtie and can include a highly-attenuating bowtie (HB) and a weakly-attenuating bowtie (WB). The HB can be filled with a liquid, and the WB can be immersed in the liquid of the HB.