Density nodule detection in 3-D digital images

• US 20020141627A1
• Filed: 11/23/2001
• Published: 10/03/2002
• Est. Priority Date: 07/10/1996
• Status: Active Grant

• Current Assignee: MeVis Medical Solutions AG (Varex Imaging Corporation)
• Original Assignee: R2 Technology, Inc. (Hologic Incorporated)
• Inventors: Zhang, Wei, Schneider, Alexander C., Romsdahl, Harlan M.
• Granted Patent: US 6,909,797 B2
• Time in Patent Office: Days
• US Class Current: 382/131
• CPC Class Codes: A61B 6/032 Transmission computed tomography [CT]
• CPC Class Codes: A61B 6/466 adapted to display 3D data
• CPC Class Codes: A61B 6/502 for diagnosis of breast, i.e. mammography
• CPC Class Codes: G06F 2203/04805 Virtual magnifying lens, i.e. window or frame movable on top of displayed information to enlarge it for better reading or selection
• CPC Class Codes: G06F 3/0481 based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
• CPC Class Codes: G06F 3/04855 Interaction with scrollbars
• CPC Class Codes: G06T 15/08 Volume rendering
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06V 10/25 Determination of region of interest [ROI] or a volume of interest [VOI]
• CPC Class Codes: G06V 10/36 Applying a local operator, i.e. means to operate on image points situated in the vicinity of a given point; Non-linear local filtering operations, e.g. median filtering
• CPC Class Codes: G06V 10/457 by analysing connectivity, e.g. edge linking, connected component analysis or slices
• CPC Class Codes: G06V 2201/03 Recognition of patterns in medical or anatomical images

Abstract

An algorithm is quickly scans a digital image volume to detect density nodules. A first stage is based on a transform to quickly highlight regions requiring further processing. The first stage operates with somewhat lower sensitivity than is possible with more detailed analyses, but operates to highlight regions for further analysis and processing. The transform dynamically adapts to various nodule sizes through the use of radial zones. A second stage uses a detailed gradient distribution analysis that only operates on voxels that pass a threshold of the first stage.

Claims

1. A method of scanning an image to detect regions of interest comprising the steps of:

calculating 3-D gradient vectors for voxels in a window of interest of the image;

applying a transform to the gradient vectors to create a transform output;

classifying the transform output into output regions, which such regions represent a different range of gradient intensity values and a different range of probabilities concerning the direction of a gradient vector;

measuring the number of directed gradients associated with the output regions'"'"'

classifying the output

2. A method of detecting 3-D masses in a digital volume created from digital images, comprising the steps of:

computing gradient planes from said digital images;

processing information from said gradient planes for identifying masses in said digital volume by applying a transformation to said gradient planes.