General Electric Company

Ge Security, Inc.

Paulo Ricardo Mendonca

Robert August Kaucic

Peter Henry Tu

Ali Can

Rahul Bhotika

Saad Ahmed Sirohey

James Vradenburg Miller

Zhaohui Harry Sun

Joseph Manuel Portaz

Fei Zhao

Harvey E Cline

Bruno Kristiaan Bernard De Man

Jens Rittscher

Zhye Yin

Thomas Baby Sebastian

Christopher Allen Nafis

Patrick Joseph Howard

Kai Zeng

Matthew William Turek

Dirk Ryan Padfield

Chandan Kumar Mallappa Aladahalli

Xiaodong Tao

Nils Oliver Krahnstoever

Shubao Liu

Andrew Frank Ferro

Brian William Thomsen

John Charles Janning

Wesley David Turner

Xingwei Yang

James Chapman Ross

Tony Chishao Pan

Theresa Rose Broniak

Jingbin Wang

Harvey Ellis Cline

Systems and methods for determining parameters for image analysis are provided. One method includes obtaining ultrasound data of an object, generating an image of the object, and identifying a region of interest in the image. The method also includes determining a plurality of spatially varying parameters for image analysis of the region of interest using prior information for one or more objects of interest, including prior location information for the one or more objects of interest, and wherein the plurality of spatially varying parameters are determined for a plurality of sections of the region of interest and different for at least some of the plurality of sections. The method further includes using the plurality of spatially varying parameters for performing image analysis of the region of interest in the image to determine the location of the one or more objects of interest.

Systems and methods for determining parameters for image analysis

A system and method for CT projection extrapolation are provided. The method comprises receiving a CT projection for extrapolation. The method also comprises selecting a target patch comprising at least one pixel of a row to be extrapolated. The method further comprises generating a correlation profile between the target patch and one or more source patches, wherein the source patches comprise measured pixels in the CT projection in one or more rows adjacent to the target patch. The projection data is generated for at least one pixel of the target patch based on the correlation profile and the measured pixels of at least one of the source patches.

Methods and systems for CT projection domain extrapolation

A method and system for visualizing regions in an image is provided. The method comprises computing a regional response around a region in the image, deriving a region score based on from the regional response for the region and labeling the region in the image by comparing the region score to a plurality of probabilistic models.

Method and system for identifying regions in an image

A method of automatic defect recognition includes receiving a initial set of inspection image data of a scanned object from a scanning machine; applying a first image analysis algorithm to this set of inspection image data; then removing from the set of inspection image data any defect-free image regions, so as to retain a set of analyzed inspection image data; applying an additional image analysis algorithm(s) to the set of analyzed inspection image data, wherein the additional algorithm(s) has a higher computational cost than the first image analysis algorithm; and based on the applying of the additional image analysis algorithm(s), removing from the first set of inspection image data a second set of defect-free image regions, thereby retaining a set of twice-analyzed inspection image data.

Sequential approach for automatic defect recognition

An imaging system includes an x-ray source configured to emit a beam of x-rays toward an object to be imaged, a detector configured to receive x-rays that are attenuated by the object, a data acquisition system (DAS) operably coupled to the detector, and a computer operably coupled to the DAS and programmed to obtain scan data with two or more incident energy spectra, decompose the obtained scan data into at least three basis materials, generate an image of one of the at least three basis materials using the decomposed scan data, and replace at least one pixel in the image using decomposed data of another of the at least three basis materials.

Apparatus and method of visualizing multi-energy imaging data

A method for identifying defects in radiographic image data corresponding to a scanned object is provided. The method includes acquiring radiographic image data corresponding to a scanned object. In one embodiment, the radiographic image data includes an inspection test image and a reference image corresponding to the scanned object. The method includes identifying one or more regions of interest in the reference image and aligning the inspection test image with the regions of interest identified in the reference image, to obtain a residual image. The method further includes identifying one or more defects in the inspection test image based upon the residual image and one or more defect probability values computed for one or more pixels in the residual image.

Method and system for identifying defects in radiographic image data corresponding to a scanned object

The present disclosure relates to the use of probabilistic models to classify elements of a medical image into different tissue types. The models may be based upon geometric abstractions of the different tissue types being classified. In addition, the present disclosure teaches the derivation and modification of models for tissue classification based upon the neighboring region of the voxels undergoing classification.

Tissue classification in medical images

An anomaly detection method includes acquiring image data corresponding to nondestructive testing (NDT) of a scanned object. The NDT image data comprises at least one inspection test image of the scanned object and multiple reference images for the scanned object. The anomaly detection method further includes generating an anomaly detection model based on a statistical analysis of one or more image features in the reference images for the scanned object and identifying one or more defects in the inspection test image, based on the anomaly detection model.

Method and system for identifying defects in NDT image data

Methods and systems for segmenting images, wherein the image pixels are categorized into a plurality of subsets using one or more indexes, then a log-likelihood function of one or more of the indexes is determined, and one or more maps are generated based on the determination of the log-likelihood function of one or more of the indexes.

Automated segmentation of image structures

A method of image reconstruction comprising: obtaining a Helmholtz reciprocal pair of images of an object, the images comprising a first image and a corresponding reciprocal image; determining an imaging geometry associated with the obtaining; selecting a plurality of points in the first image and identifying corresponding candidate points in the corresponding reciprocal image; matching a selected point of the plurality of points and a candidate point of the corresponding candidate points. A method of image registration with an object comprising: obtaining a Helmholtz reciprocal pair of images of an object, the Helmholtz reciprocal pair of images comprising a first image and a corresponding reciprocal image; estimating a pose for the object; predicting an estimated image corresponding to the pose and one image of the reciprocal pair of images; comparing the estimated image with a corresponding actual image from the pair of images; and refining the estimating a pose based on the comparing.

Surface reconstruction and registration with a helmholtz reciprocal image pair

A method for calibrating a projective camera is provided. The method includes acquiring information by detecting at least one object on a substantially flat ground plane within a field of view. A projective camera calibration is performed. A measurement uncertainty is considered to yield a plurality of camera parameters from the projective camera calibration.

Method and system for camera autocalibration

A method and system for measuring disease relevant tissue changes for use in quantifying, diagnosing and predicting a given disease are provided. The method comprises applying at least one segmenting process to the image data to generate a plurality of segmented regions of interest, extracting features relevant for a given disease from the segmented regions to generate extracted features, and mathematically modeling the features for use in one of diagnosing, quantifying and predicting changes indicative of the given disease. The system comprises an imaging device for acquiring the image data and an image process configured to segment, extract and mathematically model disease relevant features.

Method and system for measuring disease relevant tissue changes

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Clifton Park, NY, United States of America

Paulo Ricardo Mendonca