General Electric Company

Ge Medical Systems Global Technology Company, LLC

Ge Medical Systems Group, LLC

Matthew William Turek

James Vradenburg Miller

Gopal Biligeri Avinash

Peter Henry Tu

Robert August Kaucic

Joseph Leagrand Mundy

Paulo Ricardo Dos Santos Mendonca

Matthew E Ellis

William M Stoval

William J Bridge

Xiaoye Wu

Jerome F Knoplioch

William E Lorensen

Ricardo Scott Avila

Dirk Ryan Padfield

Colin Craig McCulloch

Paulo Ricardo Mendonca

David Matthew Deaven

William Murray Stoval, Iii

David P Edwards

Tony Chishao Pan

Alexis Vapillon

Tony Chi-shao Pan

Shannon Lee Hastings

An imaging system for correcting a bias in the location edges in an image is provided. The imaging system comprises an image processor configured to detect edges in an image of a given substructure, characterize a blurring factor in the image and correct a bias in the detected edges in the of a given substructure using the blurring factor.

Edge detection and correcting system and method

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.

Methods and apparatus for processing image data to aid in detecting disease

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

A method for measuring tubular anatomical structures, for example lung airways, comprises isolating by at least one segmentation process a given tubular anatomical structure of interest and measuring at least one attribute of the structure of interest. A system for measuring lung airways using acquired image data is provided. The system comprises an imaging device for acquiring the image data and an image processing device coupled to the imaging device. The imaging processing device is configured for isolating by at least one segmentation process a given airway of interest, fitting an inner ellipse to an inner boundary of the given airway and an outer ellipse to an outer boundary of the airway structure using statistical techniques at a given point in the airway, and further configured for generating measurements of the given airway using the inner and outer ellipses.

Method and system for airway measurement

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.

Method and system for lung disease detection

A method and apparatus is provided for segmenting a left ventricular endocardium in a magnetic resonance image. Image shape, size, gradients, intensity, and connectivity are used to locate the endocardial boundary. Specifically, a series of dilations and refinements to a mask corresponding to acquired data is performed. Variations in intensity, representing the endocardial boundary, are detected, and the endocardial boundary may then be clearly identified in the MR image.

Method and apparatus for extracting a left ventricular endocardium from MR cardiac images

A method and apparatus is provided for producing a smooth closed curve from a binary mask such as the type produced when segmenting various parts of a human body. Points defining the segmentation boundary are transformed into a set of polar coordinates. The set of coordinates is thresholded and averaged, and then smoothed using a window smoothing technique. The resulting boundary points are curve fit to produce the smooth closed curve.

Method and apparatus for fitting a smooth boundary to segmentation masks

A method and apparatus is provided for segmenting a left ventricular epicardium in a magnetic resonance image. Image shape, gradients, and intensity are used to locate the epicardial boundary. Specifically, an intensity map corresponding to acquired data is produced and refined so as to produce a classification map having variations in intensity. The variations, representing the epicardial boundary, are detected and the epicardial boundary may then be clearly identified in the MR image.

Method and apparatus for segmentation of a left ventricular epicardium

An method for automatically extracting a three-dimensional sub-structure, for example a coronary vessel tree, from a plurality of slice images comprises the steps of depositing a seed point within a selected region of interest and segmenting the plurality of slice images responsive to the deposition of the seed point. The segmentation is performed in accordance with a plurality of predetermined classification values to extract the three-dimensional sub-structure. A method for automatically segmenting comprises the steps of receiving a deposited seed point, extracting a plurality of desired regions within the sub-structure and generating a segmented sub-structure from the extracted desired regions.

Method for automatic segmentation of medical images

The present invention, in one form, is a system for simultaneously displaying an image object generated from an imaging system and a graphical object so that each object is fully visible. More specifically, after generating the image object, a graphical object is generated having a partial opacity value. The image object and graphical object are then sorted and combined so that the graphical object is in front of, or overlays, the image object without blocking or obscuring the information included in the image object. Particularly, a final image is generated by combining a destination value for components of each object.

Semi-transparent medical image overlays

A method for processing partial lines of image data from a detector, each partial line of data representing a portion of an image pixel matrix, includes: (a) communicating partial lines of image data over a network from an imaging system to a remote facility; (b) receiving partial lines of image data in a first sequence; (c) assigning to each partial line of image data in a first series a position in a second sequence by reference to a plurality of base addresses; (d) altering the base addresses; and (e) assigning to each partial line of image data in a second series a position in the second sequence by reference to the altered base addresses.

Method and apparatus for processing partial lines of scanned images and communicating associated data over a network

A graphic workstation receives digitized medical images and the user creates textual information that is to be displayed on the images. Instead of overlaying the text, the text data is blended with the image data such that the text appears semi-transparent and when displayed the underlying image data may be seen. The medical image may be fully restored from the blended image by a calculation based upon the blended image, the text data and alpha.

Display of text on medical images

A graphic workstation receives digitized medical images and the user creates textual information that is to be displayed on the images. The text along with associated properties are packaged as a data structure along with a set of properties, and the data structure is passed through a pipeline having a series of formatters. The formatters are easily configured by the user to modify the properties of the text data structures as they flow through the pipeline prior to being rendered on a display.

Processing text for display on medical images

Partial lines of data representative of adjacent pixels in an image pixel matrix are reordered to facilitate reconstitution of a scanned image. The partial lines are received by a signal processing circuit and are assigned unique addresses by reference to base address and offset values. Each partial line is then stored in a memory address corresponding to the assigned address. The values of the base addresses and offsets may be altered to accommodate different image matrix sizes and scanning patterns.

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Glenville, NY, United States of America

Matthew William Turek