Patrick C Heffernan, 90Watsonville, CA

7237199, Jun 26, 2007

May 30, 2000

09/580163

Wido Menhardt - Los Gatos CA, US
Patrick Heffernan - Santa Clara CA, US

Cedara Software Corp. - Mississauga, Ontario

G06F 3/00
G06F 15/16

715736, 715853, 715854, 709217

The present invention discloses a framework for monitoring workflow within an application having multiple levels of functionality, the framework being capable of combining a plurality of components from different sources and comprising a process level for selecting a set of defined process steps to be applied to a data set associated with a set of activities, a sub-process level including an aggregation of selected activities from the set of activities and facilitating navigation between the selected activities, and an activity level wherein an activity's property in the data set is modified as a result of the applied processing of the activity level to produce an output data set.

7593561, Sep 22, 2009

Nov 22, 2005

11/284570

Daoxian H. Zhang - Los Gatos CA, US
Patrick B. Heffernan - Campbell CA, US
Yue Shen - Santa Clara CA, US

Carestream Health, Inc. - Rochester NY

G06K 9/00
G06K 9/46
G06K 9/20
A61B 6/04

382130, 382132, 382190, 382283, 378 37

A method for computer-aided detection of microcalcification clusters using a digital computer obtains digital mammography data for a single view image and normalizes and filters the image data to reduce noise. A first mask is generated and applied to the image data for defining the breast structure, forming a first cropped image. A second mask is generated and applied to the image data for defining muscle structure, forming a second cropped image. An artifact mask corresponding to vascular calcifications and known imaging artifacts is generated and applied to the first and second cropped images, defining first and second artifact-masked cropped images. In a repeated sequence, portions of each artifact-masked cropped image are processed using an enhancement algorithm and reducing edge effects to obtain a set of microcalcification cluster candidates and suspected microcalcification clusters. Image processing algorithms remove false positives from the listing of microcalcification clusters and classify candidate microcalcification clusters to identify true positives.

7945083, May 17, 2011

May 25, 2006

11/440929

Daoxian H. Zhang - Los Gatos CA, US
Patrick B. Heffernan - Campbell CA, US
Marco Bucci - Genoa, IT
Zhimin Huo - Pittsford NY, US

Carestream Health, Inc. - Rochester NY

G06K 9/00
A61B 5/05

382132, 600407

A method for supporting diagnostic workflow from a medical imaging apparatus. A set of at least two images are obtained from a patient and displayed according to a user-specified image display layout selected from a plurality of image display layouts. One or more markers are associated with a region of interest in the displayed images. A list of regions of interest is generated, each having an entry for each associated marker. A classification is assigned to each entry in the list of regions of interest according to health risk.

8086002, Dec 27, 2011

Apr 9, 2008

12/099785

Heidi Daoxian Zhang - Los Gatos CA, US
Patrick Bernard Heffernan - Los Gatos CA, US

Three Palm Software - Los Gatos CA

G06K 9/00

382128, 382129, 382130, 382131

The present invention provides a method for selecting mass density candidates from digital image, for example mammograms, for computer-aided lesion detection, review and diagnosis. A method of selecting mass density candidates from a digital image for computer-aided cancer detection, review and diagnosis includes down-sampling the digital image to a low resolution; smoothing an edge along a skinline; applying a Gaussian difference filter to enhance intensity to form a filtered image; masking the filtered image using a breast mask; using a Canny detector to find potential mass density contours; and generating a mass density candidate list from Canny contours produced in the Canny detector.

8184890, May 22, 2012

Dec 26, 2008

12/344451

Heidi Daoxian Zhang - Los Gatos CA, US
Patrick Bernard Heffernan - Los Gatos CA, US

Three Palm Software - Los Gatos CA

G06K 9/00

382131, 382128, 128922

The present invention provides a method and system using computer-aided detection (CAD) algorithms to aid diagnosis and visualization of tomosynthesis mammography data. The proposed CAD algorithms process two-dimensional and three-dimensional tomosynthesis mammography images and identify regions of interest in breasts. The CAD algorithms include the steps of preprocessing; candidate detection of potential regions of interest; and classification of each region of interest to aid reading by radiologists. The detection of potential regions of interest utilizes two dimensional projection images for generating candidates. The resultant candidates in two dimensional images are back-projected into the three dimensional volume images. The feature extraction for classification operates in the three dimensional image in the neighborhood of the back-projected candidate location. The forward-projection and back-projection algorithms are used for visualization of the tomosynthesis mammography data in a fashion of synchronized MPR and VR.

8296247, Oct 23, 2012

Mar 22, 2008

12/053600

Heidi Daoxian Zhang - Los Gatos CA, US
Patrick Bernard Heffernan - Los Gatos CA, US

Three Palm Software - Los Gatos CA

G06F 15/18
G06F 15/00
G06E 1/00
G06E 3/00
G06N 99/00
G06N 5/00
G06G 7/00

706 12, 706 10, 706 45, 706924

A method of reviewing medical images and clinical data to generate a diagnosis or treatment decision is provided. The method includes receiving, at a computer-aided detection (CAD) system, the medical images and clinical data, processing the medical images and clinical data; to generate initial finding candidates and clustering the initial finding candidates into a plurality of groups. The method further includes classifying the initial finding candidates using machine learning algorithms integrated into the CAD system into one or more categories one or more categories of the initial finding candidates using type 2 fuzz logic, and determining detection and assessment statistics based on at least the assessed categories and classified findings using Bayesian probability analysis. The method also includes modifying the classified findings and assessed categories based on additional interactive input, and generating the diagnosis or treatment decision based on the determined detection, assessment statistics, and the additional interactive input.

8340387, Dec 25, 2012

Mar 23, 2008

12/053609

Heidi Daoxian Zhang - Los Gatos CA, US
Patrick Bernard Heffernan - Los Gatos CA, US

Three Palm Software - Los Gatos CA

G06K 9/00
A61B 6/04

382132, 382131, 378 4, 378 37

A method and apparatus are disclosed for an image preprocessing device that automatically detects chestwall laterality; removes border artifacts; and segments breast tissue and pectoral muscle from digital mammograms. The algorithms in the preprocessing device utilize the computer cache, a vertical Sobel filter and a probabilistic Hough transform to detect curved edges. The preprocessing result, along with a pseudo-modality normalized image, can be used as input to a CAD (computer-aided detection) server or to a mammography image review workstation. In the case of workstation input, the preprocessing results improve the protocol for chestwall-to-chestwall image hanging, and support optimal image contrast display of each segmented region.

8208700, Jun 26, 2012

May 12, 2008

12/119295

Heidi Daoxian Zhang - Los Gatos CA, US
Patrick Bernard Heffernan - Los Gatos CA, US

Three Palm Software - Los Gatos CA

G06K 9/00
G06K 9/34
A61B 6/04

382128, 382173, 378 37

The present invention provides an algorithm to detect and trace the spicules of a mass density in digital mammograms using an adaptive threshold edge algorithm and a flood-fill segmentation algorithm. Elongation criteria are used to remove false edges that do not radiate from a central mass margin. The algorithm works on a central mass border and spicules feature map that contains a subset of the pixels from the source image, so processing time is fast enough for use in a mammography CAD server and for real-time computation within a digital mammography workstation.