Medical School U Of Chgo Div Of Bio Sci Pritzker Sch Of Med Graduated: 1975 Medical School Virginia Commonwealth University Medical Center Graduated: 1975 Medical School Natl Heart-Lung-Blood Inst Graduated: 1975 Medical School University Of Washington Graduated: 1975
Richard Johnson - Sammamish WA, US John McDonald - Seattle WA, US Florence Sheehan - Mercer Island WA, US
International Classification:
G06T017/00
US Classification:
345/420000
Abstract:
A method for fitting a surface to some portion of a patient's heart. In the method, ultrasound imaging is carried out over at least one cardiac cycle, providing a plurality of images in different image planes made with a transducer at known positions and orientations. An operator selects points on some of the images that correspond to the surface of interest, and a surface is automatically fit to the points in three dimensions, using prior knowledge about heart anatomy to constrain the fitted shape to a reasonable result. The operator reviews the fitted surface, in 3D or alternatively, as intersected with the images. If the fit is acceptable, the process is done. Otherwise, the image processing is repetitively carried out, guided by the fitted surface, to produce additional data points, until an acceptable fit is obtained. The resulting output surface can be used in determining cardiac parameters.
Segmentation Of Left Ventriculograms Using Boosted Decision Trees
John McDonald - Seattle WA, US Florence Sheehan - Mercer Island WA, US
International Classification:
G06K009/00 G06K009/48
US Classification:
382128000, 382199000
Abstract:
An automated method for determining the location of the left ventricle at user-selected end diastole (ED) and end systole (ES) frames in a contrast-enhanced left ventriculogram. Locations of a small number of anatomic landmarks are specified in the ED and ES frames. A set of feature images is computed from the raw ventriculogram gray-level images and the anatomic landmarks. Variations in image intensity caused by the imaging device used to produce the images are eliminated by de-flickering the image frames of interest. Boosted decision-tree classifiers, trained on manually segmented ventriculograms, are used to determine the pixels that are inside the ventricle in the ED and ES frames. Border pixels are then determined by applying dilation and erosion to the classifier output. Smooth curves are fit to the border pixels. Display of the resulting contours of each image frame enables a physician to more readily diagnose physiological defects of the heart.
Ultrasound Training And Testing System With Multi-Modality Transducer Tracking
Florence Sheehan - Mercer Island WA, US Catherine M. Otto - Seattle WA, US Edward L. Bolson - Redmond WA, US Mark D. Anderson - Stanwood WA, US
Assignee:
higher education - Seattle WA
International Classification:
G09B 23/28
US Classification:
434267
Abstract:
An apparatus and a method reproduce a diagnostic or interventional procedure that is performed by medical personnel using ultrasound imaging. A simulator of ultrasound imaging is used for purposes such as training medical professionals, evaluating their competence in performing ultrasound-related procedures, and maintaining, refreshing, or updating those skills over time.
Florence H. Sheehan - Mercer Island WA Gregory L. Zick - Kirkland WA
Assignee:
University of Washington - Seattle WA
International Classification:
H65G 160
US Classification:
378 95
Abstract:
A method and system for identifying end systole and end diastole frames within an angiography sequence. A plurality of images produced during an angiography sequence are digitized, producing digital image data in which gray scale values for each of the pixels in the images are represented. The digital image data are input to a computer (48) to determine the frames in which the coronary arteries are most visible. The coronary arteries are made visible in the images by injecting a radio-opaque contrast substance into the arteries. The frames that occur a end diastole are preferred for diagnostic analysis because the arteries are distended, spread apart from each other, and moving very slowly. To identify such frames for further analysis, the total length of edges within a centered window covering approximately one-fourth of each image is determined. The edges represent spatial transitions between relatively light and dark areas in the image that occur across the borders of the coronary arteries.
Automated Delineation Of Heart Contours From Images Using Reconstruction-Based Modeling
Florence H. Sheehan - Mercer Island WA Robert M. Haralick - Seattle WA Paul D. Sampson - Seattle WA
Assignee:
University of Washington - Seattle WA
International Classification:
A61B 800
US Classification:
600443
Abstract:
A method for defining a three-dimensional surface of at least a portion of a patient's heart, based on data obtained by ultrasound imaging of the heart. The imaging is carried out over at least one cardiac cycle and provides a plurality of images in different image planes made with an ultrasound transducer at known positions and orientations. At least three anatomical landmarks in these images are manually identified in each of the images. An ultrasound mesh model in which a three-dimensional abstract mesh defining an archetype shape for a population of other hearts is developed. This abstract mesh has associated with it a covariance that defines the extent of variation of control vertices in the mesh for the population of training data used to derive the mesh model. The mesh model is rigidly aligned with the images of the patient's heart. Predicted images in planes corresponding to those of the images for the patient's heart and derived from the mesh model are compared corresponding images of the patient's heart.
Determining Cardiac Wall Thickness And Motion By Imaging And Three-Dimensional Modeling
Florence H. Sheehan - Mercer Island WA Edward L. Bolson - Redmond WA Fred L. Bookstein - Ann Arbor MI Paul D. Sampson - Seattle WA
Assignee:
University of Washington - Seattle WA
International Classification:
A61B 500
US Classification:
1286531
Abstract:
A method for imaging and three-dimensional modeling portions of the heart, particularly, the left ventricular endocardial and epicardial surfaces, using imaging data. Preferably, a transesophageal ultrasound probe is inserted into an esophagus of a patient to provide multiple plane imaging data at end systole and end diastole during a cardiac cycle. The image planes are then traced along the boundaries of the epicardial and endocardial surfaces to produce sets of data points, which are further processed and expanded through interpolation. These data points are used for modeling the endocardial and epicardial surface at the end systole and end diastole extremes of the cardiac cycle. A center surface is constructed between an inner and outer surface of the modeled surfaces of the left ventricle and an average template of tiled sections is mapped onto this center surface. The mapped tiled sections are then projected onto the inner and outer surfaces, defining triangular prisms.
Reconstruction Of Three-Dimensional Objects Using Labeled Piecewise Smooth Subdivision Surfaces
Florence H. Sheehan - Mercer Island WA John A. McDonald - Seattle WA Edward L. Bolson - Redmond WA Malcolm E. Legget - Remeura, NZ
Assignee:
University of Washington - Seattle WA
International Classification:
G06T 1700
US Classification:
345419
Abstract:
A method is disclosed for reconstructing a surface of an object using three-dimensional imaging data. While the method can be applied to reconstruct the surface of almost any object represented by three-dimensional data obtained by some imaging modality, an example of the technique is disclosed that reconstructs the surface of a left ventricle. In the disclosed example, digital imaging data for a patient's heart are traced producing a data set of points that define the border and specific anatomic features of the left ventricle. An abstract model of a generalized left ventricle is generated that fits a wide range of sizes and shapes of this portion of the heart. The abstract model includes an abstract control mesh in which the anatomic features are labeled and sharp (edge) characteristics are identified. Coordinates are assigned to the abstract control mesh, producing an initial embedded mesh, which is then subdivided twice to increase its smoothness. The embedded subdivided mesh is rigidly aligned with the data set points of the patient's left ventricle, and in particular, with the anatomic features.
Method For Determining The Contour Of An In Vivo Organ Using Multiple Image Frames Of The Organ
Florence H. Sheehan - Mercer Island WA Robert M. Haralick - Seattle WA Chang-Kyu Lee - Seattle WA
Assignee:
University of Washington - Seattle WA
International Classification:
G06K 900
US Classification:
382128
Abstract:
A method for automatically evaluating image data taking over a sequence of image frames to determine a contour of a left ventricle (LV). The sequence of image frames are converted to digital data that identify a gray scale value for each pixel in each image frame. Using probability, an initial LV region is estimated based upon previously determined a priori parameters that are derived from processing manually drawn contours of the LV in other hearts, for the sequence of image frames being analyzed. The initial estimate of the LV region is refined using motion constraints, which are also derived from training data determined from the manually-drawn contours of other hearts. An LV region is estimated and its coordinates are extracted for use in applying global shape constraints that provide a more accurate LV boundary estimate for the region around an apex of the left ventricle. Finally, the estimated LV boundary estimate is tested for consistency, yielding an accepted estimate, or warning that the estimate is unreliable. The resulting automatically determined contours of each image frame can be displayed almost immediately after the image data are produced so that a physician can more readily diagnose physiological defects of the heart.
Name / Title
Company / Classification
Phones & Addresses
Florence H. Sheehan Managing
Huang Sheehan Properties, LLC Real Property Ownership
4510 E Thousand Oaks Blvd, Thousand Oaks, CA 91362 7835 85 Pl SE, Mercer Island, WA 98040
Florence Huang Sheehan
Florence Sheehan MD Internist
1959 NE Pacific St, Seattle, WA 98195 206-543-4535
Florence Sheehan Director
University of Washington Medical Doctor's Office College/University
Health Scences BLDG RR616, Seattle, WA 98195 206-543-4535
Florence Sheehan President
Sheehan Medical Device Corporation Surgical and Medical Instruments · Mfg Electromedical Equipment
Chief Scientist at VentriPoint, Inc., Consultant, entrepreneur, cardiologist at Various (Self-employed), Research Professor at University of Washington
Location:
Greater Seattle Area
Industry:
Medical Devices
Work:
VentriPoint, Inc. since 2005
Chief Scientist
Various since 1990
Consultant, entrepreneur, cardiologist
University of Washington since 1980
Research Professor
Quantigraphics, Inc 1996 - 2004
Chief Scientist
Education:
Dale Carnegie 1979 - 2003
University of Chicago - The Pritzker School of Medicine 1971 - 1975
MD, Medicine
Massachusetts Institute of Technology 1967 - 1971
BS, Life Science
Interests:
company startup, medical imaging, mountain climbing