| Patent application number | Description | Published |
|---|
| 20080287787 | Line-based calibration of ultrasound transducer integrated with a pose sensor - Apparatus for calibrating an ultrasound transducer providing B-scans for two-dimensional (2D) images, includes: an ultrasound probe for providing B-scans; a position sensing device, the position sensing device being attached to the ultrasound probe and operating as part of a position sensing system in cooperation with a fixed sensing control unit, for labeling the B-scans with their respective relative positions and orientations (pose); a phantom marker for being imaged by the ultrasound probe for providing measurements which together with known physical properties of the phantom marker are used to derive calibration information for relating measurement data from the position sensing device to the poses of the B-scans to construct a 3D image; and the phantom marker comprising an encoded line object with distinctive calibration characteristics indicative of position along the line object, wherein the line object is disposed in a generally circumferential manner about a common axis with the probe. | 11-20-2008 |
| 20090052757 | DEFORMABLE 2D-3D REGISTRATION - A method for deformable registration including determining a vector field from a two-dimensional matching of a volume of an object of interest and a two-dimensional image of the object of interest, providing a deformation profile, and finding a volume deformation that maps to a state of the two-dimensional image, wherein the deformation is parameterized by the vector field and control points of the deformation profile to find a control point configuration of the volume deformation. | 02-26-2009 |
| 20090067755 | SYSTEM AND METHOD FOR GEODESIC IMAGE MATCHING USING EDGE POINTS INTERPOLATION - A method for deformable registration of 2 digital images includes providing a pair of digital images, including a fixed image and a moving image, extracting a set of edge images from each image of the pair of images, each edge set being extracted at a different resolution, selecting a pair of edge images with a lowest resolution, determining a mapping from edge points of the fixed image to edge points of moving image using a geodesic thin plate spline interpolation, applying the mapping to a next higher resolution edge point image of the moving image, selecting a pair of edge images at a next higher resolution, where a moving edge image is the moving edge image to which the mapping has been applied, repeating the steps at a next higher resolution for all edge images in the set of edge images, and applying the mapping to an entire moving image. | 03-12-2009 |
| 20090088632 | Method for Dynamic Road Mapping - A method of determining a three-dimensional (3D) position of a catheter tip includes: compensating a 2D position of the tip of the catheter for respiratory motion to generate a compensated 2D catheter position, generating weighted sample points around the compensated 2D catheter position, determining correspondent points of the weighted sample points in a 3D image, computing a weighted mean and a weighted covariance of each correspondent point, and determining the 3D position of the catheter tip in the 3D image from a fusion of the weighted means and weighted covariances. | 04-02-2009 |
| 20090161928 | SYSTEM AND METHOD FOR UNSUPERVISED DETECTION AND GLEASON GRADING OF PROSTATE CANCER WHOLE MOUNTS USING NIR FLUORSCENCE - A method for unsupervised classification of histological images of prostatic tissue includes providing histological image data obtained from a slide simultaneously co-stained with NIR fluorescent and Hematoxylin-and-Eosin (H&E) stains, segmenting prostate gland units in the image data, forming feature vectors by computing discriminating attributes of the segmented gland units, and using the feature vectors to train a multi-class classifier, where the classifier classifies prostatic tissue into benign, prostatic intraepithelial neoplasia (PIN), and Gleason scale adenocarcinoma grades 1 to 5 categories. | 06-25-2009 |
| 20090285357 | Automatic Patient Positioning System - A patient positioning system for positioning a patient relative to radiographic equipment. The system includes: a 3D optical imaging system for optically scanning the patient, such 3D optical imaging system having a focal plane and providing, for each position on the object, data representative of the intensity of reflected energy received by the system from such position and data representative of distance from such position on the object to the focal plane; a table apparatus for supporting the patient and for moving the table relative to the radiographic equipment in response to positioning signals; and a processor responsive to data from the radiographic equipment and the data from the a 3D optical imaging system for producing the positioning signals. The system enables a method for displaying temporal changes in a patient positioned with a bore of radiographic equipment. | 11-19-2009 |
| 20100266170 | Methods and Systems for Fully Automatic Segmentation of Medical Images - Methods and systems dedicated to automatic object segmentation from image data are provided. In a first step a fuzzy seed set is generated that is learned from training data. The fuzzy seed set is registered to image data containing an object that needs to be segmented from a background. In a second step a random walker segmentation is applied to the image data by using the fuzzy seed set as an automatic seeding for segmentation. Liver segmentation, lung segmentation and kidney segmentation examples are provided. | 10-21-2010 |
| 20110130645 | SYSTEM AND METHOD FOR RECONSTRUCTION OF THE HUMAN EAR CANAL FROM OPTICAL COHERENCE TOMOGRAPHY SCANS - A method for reconstructing an ear canal from optical coherence tomography (OCT) scan data of an ear comprises extracting frame numbers and line numbers of interference intensities corresponding to one or more markers on an OCT scan guide, receiving reference frame numbers and lines numbers for one or more markers, determining a starting position and direction for the OCT ear scan from the ear scan marker frame and line numbers and the reference marker frame and line numbers, for each scan line, finding a pixel number of a maximum interference intensity value, and determining an offset distance of said pixel from said scan guide, and reconstructing a surface of the ear canal from the distance offset data. | 06-02-2011 |
