Analogic Corporation

Neurologica Corporation, a Subsidiary of Samsung Electronics Co., Ltd.

Samsung Electronics Co., Ltd.

Ibrahim M Bechwati

Carl R Crawford

Sergey Simanovsky

Muzaffer Hiraoglu

Ram Naidu

Philip Sullivan

Muzzafer Hiraoglu

Eric M Bailey

David Rozas

Seemeen S Karimi

Geethika Weliwitigoda

Seemee S Karimi

Matthew Christensen

Ross Caisse

A method for correcting inaccuracies in a three-dimensional (3D) rendered volume of an object due to deviations between an actual scanner translation speed and an expected scanner translation speed, the method comprising: placing a pre-measured reference adjacent to the object which is being scanned so that the pre-measured reference and the object are in the same scan field; scanning the object and the pre-measured reference so that the object and the pre-measured reference are both incorporated in a 3D rendered volume produced through scanning; comparing the 3D rendered volume of the pre-measured reference against the 3D volume of the true pre-measured reference and generating a correction map indicative of how the rendered 3D volume of the pre-measured reference should be adjusted so as to produce a more accurate 3D rendering of the pre-measured reference; and using the correction map to adjust the rendered 3D volume of the object.

AI-based rendered volume auto-correction for fixed and mobile x-ray imaging modalities and other imaging modalities

Methods for the correction of drive, tilt, and scanning-speed errors in imaging systems such as CT machines.

Correction for drive, tilt, and scanning-speed errors in imaging systems

A method for calibrating detectors in a CT scanner, wherein the new calibration process uses a combination of slab-based and water-based calibrations. By combining both calibrations, the complexity of each procedure can be reduced which will reduce restrictions on the quality of detectors used in the scanner. The slabs can be made out of commercially available material such as acrylic, and they will require no special treatment. Combining both calibrations also reduces the number of water phantoms needed for the calibration and the complexity of the calibration algorithm. Furthermore, the slabs can be shaped based on the scanner geometry so as to optimize the slab-based calibration step.

Anatomical imaging system with improved detector calibration process

A method of performing bone correction on a computerized tomography (CT) image includes the steps of:

Adaptive iterative bone correction in computerized tomography

A method of decomposition of projection data is provided, wherein such projection data includes input projection data acquired using at least two x-ray spectra for a scanned object, including low energy projection data (P) and high energy projection data (P); the method comprises solving the projections Pand Pto determine a photoelectric line integral (A) component of attenuation and a Compton line integral (A) component of attenuation of the scanned object using a multi-step fitting procedure and constructing a Compton image Iand a photoelectric image Ifrom the Compton line integral and photoelectric line integral.

Decomposition of multi-energy scan projections using multi-step fitting

A method of and apparatus for assessing the image quality of a CT scanner is described in which assessment can be made manually or automatically. No special image quality mode of CT scanner operation is necessary, and no precise alignment of the phantom is necessary. In general, performance of the scanner comprises: using the scanner (a) to scan a phantom in one or more of its normal modes of operation while translating said phantom along the scanner axis of rotation and (b) to produce scanned data of the phantom, and assessing the performance of the scanner from the scanned data. In accordance with another aspect, the assessment is performed by (a) using the scanner to scan a phantom in one or more of its normal modes of operation; (b) reconstructing a three-dimensional volume CT image for a region containing at least a portion of the phantom; (c) calculating properties of the CT image; and (d) using the calculated properties of the CT image to assess CT scanner performance.

Method and apparatus for automatic image quality assessment

Method of and system for reducing metal artifacts in images generated by x-ray scanning devices

A system for correcting for scatter in a computed tomography scanner includes a tunnel having a platform disposed therein for receiving an object to be scanned, an x-ray source for directing x-rays at the object to be scanned, a detector array including a plurality of primary detectors for receiving the x-rays and at least one secondary detector for receiving portion of the x-ray beam scattered within the tunnel. The system further includes processing means for reducing the effects of scatter in images of the object reconstructed from the x-rays detected by method of estimating an amount of scatter caused only by the presence of the object corrected by an amount of scattered x-ray when presence or absence of object.

Method of and system for correcting scatter in a computed tomography scanner

An apparatus and method for identifying and classifying objects represented in CT data for a region using the shape of the objects are disclosed. An object represented by CT data for a region is identified. Next, a two-dimensional projection of the object along a principal axis of the object is generated. The principal axis can be identified by computing eigenvectors of a covariance matrix of spatial locations of voxels in the CT data that are associated with the object. The smallest eigenvector can be selected as the principal axis of the object along which the two-dimensional projection is generated. The identification of the object can be used in the classification of the object such as by altering one or more discrimination parameters.

Apparatus and method for processing object data in computed tomography data using object projections

A method and apparatus detects sheet explosives in computed tomography (CT) data. In particular, sheet-shaped objects such as sheet explosives can be discriminated from other object shapes and detected. The detection includes analyzing a neighborhood of voxels surrounding a test voxel. If the density of the test voxel is sufficiently different from the mean density of the neighboring voxels, then it is concluded that the test voxel is associated with a sheet object. Sheet objects can also be detected by eroding the CT data so as to eliminate voxels associated with thin objects. Remaining objects are then subtracted from the original data, leaving only thin sheet-shaped objects. Erosion of the data can be performed by identifying a neighborhood of voxels surrounding a voxel of interest. If the number of voxels having densities below a predetermined threshold exceeds a predetermined number, then it is assumed that the test voxel is a surface voxel and is removed from the object. A connectivity process can be applied to voxels to combine them into objects after sheets are detected to prevent sheets from being inadvertently removed from the data by erosion. A dilation function can then be performed on the eroded object to replace surface voxels removed by erosion. A corrected mass using the mean eroded density of the object can be computed and compared to mass thresholds to classify the object as to whether it poses a threat. Multiple mass thresholds can be used, each of which is associated with a particular density range based on the density of an expected threat object.

Computed tomography apparatus and method for classifying objects

A method of and apparatus for detecting objects in computed tomography (CT) data includes the ability to define the types of objects to be detected, and at least one algorithm related to the detection of each type of object. Multiple types of objects can be detected and distinguished from one another. Each type of object exhibits an object detection rate related to the probability of the system detecting the corresponding object type, and a false detection rate related to the false identification of objects, different from the target objects, as the target objects. An overall system detection rate is related to a combination of the object detection rates. Each type of object can also be associated with a unique object false alarm rate, with a overall false detection rate being related to the combination of object false alarm rates. The overall system and/or object detection rate, and/or the false alarm rate and/or the overall false detection rate can be optimized by modifying at least one algorithm so as to adjust at least one of the object detection rates or object false alarm rate.

Apparatus and method for optimizing detection of objects in computed tomography data

A method and apparatus for detecting concealed objects in computed tomography data are disclosed. Sheet-shaped objects such as sheet explosives can be detected by a CT scanning system, in particular, a CT baggage scanning system. The invention analyzes CT voxels in a subregion in proximity to the sheet object to determine if the sheet object is concealed in an electronic device or is &ldquo;sandwiched&rdquo; within an item such as a book or magazine. To detect electronic concealment, the number of voxels in a subregion that contains the object having a density above a predetermined threshold is counted and the ratio of that number of voxels to the number of object voxels is computed. If the ratio exceeds a threshold, then it is concluded that the object is concealed in electronics. In response, the CT scanning system can alter discrimination parameters to allow the object to be classified as a threat. For &ldquo;sandwich&rdquo; concealment, layers on opposite sides of a sheet object are examined. The mean and standard deviation of density values for the voxels are computed. Where the mean density exceeds a predetermined threshold and the standard deviation is below a different threshold, for at least one of the layers, then it is concluded that the sheet object is sandwiched within an innocuous object such as a magazine or a book.

Apparatus and method for detecting concealed objects in computed tomography data

A system for and method of detecting and classifying objects contained within or concealed by items scanned by an X-ray scanner is described. Greater throughput and relatively reduced cost is achieved by using a shared bulk memory for entering imaging data received from the scanner into slots of a bulk shared memory; and storing detection and classification data in slots of the bulk memory after processing imaging data so as to provide detection and classification data relating to absence or suspected presence of predetermined target objects. Preferably, the scanner is a CT scanner and the imaging data is CT data.

Architecture for CT scanning system

Sheet-shaped objects can be detected by analyzing a neighborhood of voxels surrounding a test voxel. If the density is sufficiently different, then the voxel is associated with a sheet object. Sheet objects can also be detected by eroding the CT data so as to eliminate voxels associated with thin objects. Remaining objects are then subtracted from the original data, leaving only thin sheet-shaped objects. If the number of voxels having densities below a predetermined threshold exceeds a predetermined number, then it is assumed that the test voxel is a surface voxel and is removed from the object. A connectivity process can be applied to voxels to combine them into objects after sheets are detected. A dilation function can then be performed to replace surface voxels. A corrected mass can be compared to mass thresholds. Bulk objects can be detected by a modified morphological connected components labeling (CCL) approach. A merging process can be used to reconnect related items. The system can also identify objects that contain liquids. The object detection rate and false alarm rate can be adjusted by adjusting individual object detection rates and/or false alarm rates.

Apparatus and method for combining related objects in computed

A method and apparatus for detecting objects in computed tomography (CT) data, including sheet-shaped objects such as sheet explosives can be detected by analyzing a neighborhood of voxels surrounding a test voxel. If the density of the test voxel is sufficiently different from the mean density of the neighboring voxels, then it is concluded that the test voxel is associated with a sheet object. A connectivity process can be applied to voxels to combine them into objects after sheets are detected to prevent sheets from being inadvertently removed from the data by erosion.

Growing community of inventors

Roslindale, MA, United States of America

Ibrahim M Bechwati