Abstract: An anomaly detection method and system for comparing a scanned object to an idealized object is provided. The anomaly detection method includes generating a three-dimensional reference model of the idealized object. The anomaly detection method further includes acquiring at least one two-dimensional inspection test image of the scanned object. The anamoly detection method also includes determining a two-dimensional reference image from the three-dimensional reference model using multiple pose parameters, wherein the two-dimensional reference image corresponds to the same view of the three-dimensional reference model of the idealized object as the view of the two-dimensional inspection test image of the scanned object. The anamoly detection method further includes identifying one or more defects in the inspection test image via automated defect recognition technique.

Abstract: A method for determining 3D distances on a 2D pixelized image of a part or object includes acquiring a real 2D pixelized image of the object, creating a simulated image of the object using the 3D CAD model and the 2D pixelized image, determining a specified cost function comparing the simulated image with the real 2D pixilated image and repositioning the simulated image in accordance with iterated adjustments of a relative position between the CAD model and the XID pixilated image to change the simulated image until the specified cost function is below a specified value. Then, the workstation is used to generate a 3D distance scale matrix using the repositioned simulated image, and to measure and display distances between selected pixels on a surface of the real image using 2D distances on the 2D pixelized image of the object and the 3D distance scale matrix.

Abstract: 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.

Abstract: 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.

Abstract: A method for automatically identifying defects in turbine engine blades is provided. The method comprises acquiring one or more radiographic images corresponding to one or more turbine engine blades and identifying one or more regions of interest from the one or more radiographic images. The method then comprises extracting one or more geometric features based on the one or more regions of interest and analyzing the one or more geometric features to identify one or more defects in the turbine engine blades.

Abstract: A system and method for ascertaining the identity of an object within an enclosed article. The system includes an acquisition subsystem utilizing a stationary radiation source and detector, a reconstruction subsystem, a computer-aided detection (CAD) subsystem, and a 2D/3D visualization subsystem. The detector may be an energy discriminating detector. The acquisition subsystem communicates view data to the reconstruction subsystem, which reconstructs it into image data and communicates it to the CAD subsystem. The CAD subsystem analyzes the image data to ascertain whether it contains any area of interest. Any such area of interest data is sent to the reconstruction subsystem for further reconstruction, using more rigorous algorithms and further analyzed by the CAD subsystem. Other information, such as risk variables or trace chemical detection information may be communicated to the CAD subsystem to be included in its analysis.

Abstract: A system for determining a track location operates to acquire a current video frame via at least one video camera mounted on board a locomotive, determine a track location based on information extracted from the at least one video frame, and transmit the track location information to a navigation system to determine control parameters for the locomotive.

Abstract: A method of improving a signal to noise ratio of an image data set of a cargo container is disclosed. The method includes transmitting a radiation beam toward the cargo container, detecting the transmitted radiation beam via a plurality of area radiation detectors, each area radiation detector comprising an active area defined by a matrix of pixels, thereby defining enhanced radiation data, processing the enhanced radiation data and reconstructing the image data set representative of contents of the cargo container, combining image attributes of the image data set to improve the signal to noise ratio, thereby defining an enhanced image data set, and displaying on a display the enhanced image data set comprising an improved signal to noise ratio.

Abstract: A method for detecting, quantifying, staging, reporting, and/or tracking of a disease includes providing analysis software configured to detect, quantify, stage, report, and/or track a disease utilizing images of a patient. The analysis software is executable on a personal computer of a patient. Patients are then imaged utilizing a medical imaging apparatus and medical images of the patient produced by the imaging apparatus are downloaded to the personal computer of the patient. The imaging and downloading are repeated a plurality of times at intervals selected to provide the analysis software with sufficient images to detect, quantify, stage, report, and/or track the disease in the patient.

Abstract: 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.

Abstract: A method for processing medical images for use in the detection and diagnosis of disease comprises classifying regions of interest within the medical images based on a hierarchy of anatomical models and signal models of signal information of an image acquisition device used to acquire the medical images. The anatomical models are derived to be representative of anatomical information indicative of a given disease. A computer-aided system for use in the diagnosis and detection of disease comprises an image acquisition device for acquiring a plurality of image data sets and a processor adapted to process the image data sets. The processor is adapted to classify selected tissue types within the image data sets based on a hierarchy of signal and anatomical models and the processor is further adapted to differentiate anatomical context of the classified tissue types for use in the diagnosis and detection of disease.

Abstract: A system and a method for detecting an object, such as an explosive device or material, located within a closed article, such as a piece of luggage or a parcel. The system includes an acquisition subsystem for acquiring information pertaining to a specific object, a reconstruction subsystem for reconstructing acquired information pertaining to the specific object into image data, and a computer-aided detection subsystem adapted for identifying the specific object through the use of differential operators. The method includes obtaining image data of the one object, computing a differential operator for each voxel of the image data, computing eigenvalues and eigenvectors for each of the voxels, and computing a scalar function of the eigenvalues to ascertain whether each of the voxels represents a portion of the one object.

Abstract: A method for detecting, quantifying, staging, reporting, and/or tracking of a disease includes providing analysis software configured to detect, quantify, stage, report, and/or track a disease utilizing images of a patient. The analysis software is executable on a personal computer of a patient. Patients are then imaged utilizing a medical imaging apparatus and medical images of the patient produced by the imaging apparatus are downloaded to the personal computer of the patient. The imaging and downloading are repeated a plurality of times at intervals selected to provide the analysis software with sufficient images to detect, quantify, stage, report, and/or track the disease in the patient.

Abstract: 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.

Abstract: A method for processing medical images for use in the detection and diagnosis of disease comprises classifying regions of interest within the medical images based on a hierarchy of anatomical models and signal models of signal information of an image acquisition device used to acquire the medical images. The anatomical models are derived to be representative of anatomical information indicative of a given disease. A computer-aided system for use in the diagnosis and detection of disease comprises an image acquisition device for acquiring a plurality of image data sets and a processor adapted to process the image data sets. The processor is adapted to classify selected tissue types within the image data sets based on a hierarchy of signal and anatomical models and the processor is further adapted to differentiate anatomical context of the classified tissue types for use in the diagnosis and detection of disease.