Virginia Tech Intellectual Properties, Inc.

Rensselaer Polytechnic Institute

University of Massachusetts

University of Iowa Research Foundation

Hengyong Yu

Ge Wang

Wenxiang Cong

Alexander Katsevich

Jun Zhao

Yang Lu

Yaguang Luo

Fenglin Liu

Yangbo Ye

Jiansheng Yang

Weiwen Wu

Boce Zhang

Xiaobo Liu

Generally, there is provided a hybrid image reconstruction system. The hybrid image reconstruction system includes a deep learning stage and a compressed sensing stage. The deep learning stage is configured to receive an input data set that includes measured tomographic data and to produce a deep learning stage output. The deep learning stage includes a mapping circuitry, and at least one artificial neural network. The mapping circuitry is configured to map image domain data to a tomographic data domain. The compressed sensing stage is configured to receive the deep learning stage output and to provide refined image data as output.

Hybrid image reconstruction system

A chromogenic assay includes a substrate comprising an array of 5 or more dyes which react with volatile organic compounds, wherein the dyes are chromogenic when reacted with volatile organic chemical biomarkers, wherein the volatile organic chemical biomarkers comprise acids, alcohols, aldehydes, alkenes, amines, antioxidants, aromatic compounds, esters, ethylene, lactones, ketones, organosulfur compounds, sulfides, reactive oxygen species, terpenes, or a combination thereof. A method of detecting volatile organic chemical biomarkers includes contacting the chromogenic assay with a sample or sample headspace, wherein the sample or sample headspace is suspected of containing volatile organic chemical biomarkers, and identifying, based on a colorimetric pattern on the chromogenic assay after contacting, the source of the volatile organic chemical biomarkers. Also included are articles and systems including the chromogenic assay.

Method and system for chromogenic array-based food testing

Imaging methods and imaging systems are provided. Methods and systems of the subject invention can include linearly translating a source and a detector. The source and the detector can be moved in opposite or approximately opposite directions. Acquired data can be used to reconstruct a tomographic image by using, for example, a compressive sensing technique.

Computed tomography based on linear scanning

The present invention provides systems, methods, and devices for improved computed tomography (CT) and, more specifically, to methods for improved single photon computed tomography (SPECT) using exact and stable region of interest (ROI) reconstructions. This technology can be extended across all tomographic modalities. Embodiments provide a method and a system for reconstructing an image from projection data provided by a single photon emission computed tomography scanner comprising: identifying a region of interest in an object; defining an attenuation coefficient and object boundary; computing the generalized Hilbert transform of the data through the defined region of interest and a known subregion; and reconstructing the image with improved temporal resolution at lower radiation doses, wherein the reconstructing comprises performing a reconstruction method that yields an exact and stable reconstruction. Embodiments also provide a method and a system for reconstructing an image from projection data provided by a single photon emission computed tomography scanner comprising: identifying a region of interest in an object; defining an attenuation coefficient and object boundary; and reconstructing the images by minimizing the high order total variation while minimizing the data discrepancy.

Methods for improved single photon emission computed tomography using exact and stable region of interest reconstructions

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.

Exact local computed tomography based on compressive sampling

The present invention provides systems, methods, and devices for improved computed tomography (CT). More specifically, the present invention includes methods for improved cone-beam computed tomography (CBCT) resolution using improved filtered back projection (FBP) algorithms, which can be used for cardiac tomography and across other tomographic modalities. Embodiments provide methods, systems, and devices for reconstructing an image from projection data provided by a computed tomography scanner using the algorithms disclosed herein to generate an image with improved temporal resolution.

Cardiac computed tomography methods and systems using fast exact/quasi-exact filtered back projection algorithms

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.

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Winston-Salem, NC, United States of America

Hengyong Yu