Method of processing images

• US 7,162,062 B2
• Filed: 12/21/2001
• Issued: 01/09/2007
• Est. Priority Date: 12/26/2000
• Status: Expired due to Fees

• Current Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Original Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Inventors: Florent, Raoul, Breitenstein, Jacques
• Primary Examiner(s): Johns; Andrew W.
• Application Number:
  US10/028,388
• Publication Number:
  US 20020114499A1
• Time in Patent Office: 1,845 Days
• Field of Search: 382/128, 382/130, 382/132, 382/154, 382/180, 382/197, 382/199, 382/202, 382/204, 382/256, 382/257, 382/258, 382/259, 382/260
• US Class Current: 382/128
• CPC Class Codes: G06T 2207/10121 Fluoroscopy
• CPC Class Codes: G06T 2207/20044 Skeletonization; Medial axis transform
• CPC Class Codes: G06T 2207/30101 Blood vessel; Artery; Vein; Vascular
• CPC Class Codes: G06T 7/12 Edge-based segmentation
• CPC Class Codes: G06T 7/181 involving edge growing; involving edge linking
• CPC Class Codes: G06T 7/70 Determining position or orientation of objects or cameras camera calibration G06T7/80

Abstract

A method of processing images in images comprising curvilinear structures comprises, in parallel, a step of filtering said images and a decision step intended to select the pixels of the images pertaining to a curvilinear structure, the method comprising, in parallel, a sub-step of estimating the direction of each image pixel, as well as a sub-step of analyzing the connectivity of neighboring pixels based on their directions at the end of the sub-step of estimating the direction of each image pixel, and a sub-step of selecting groups of pixels as a function of the result of the sub-step of analyzing the connectivity of neighboring pixels based on their directions, at the end of the step of filtering. Such a method allows selection of curvilinear structures which are fine structures such as a catheter in a medical image, or thicker structures such as a tree-like structure of blood vessels. This method may be used, for example, in medical scanning apparatus for detecting artery anomalies such as stenosis or a diffuse coronary disease.

Claims

1. A method of processing images comprising curvilinear structures, the method comprising the steps of:

filtering said images;

selecting pixels within said images pertaining to a curvilinear structure, and

estimating a direction of each image pixel and analyzing a connectivity of neighboring pixels based on the estimated directions for each said image pixel, and

selecting groups of image pixels as a function of the result of said analizing.

2. A method of processing images as claimed in claim 1, wherein the step of filtering said images further comprises a step of selecting pixels, the selected pixels displaying a contrast which is larger than X times a variance of the noise in the image, where X is a user-adjustable parameter.

3. A method of processing images as claimed in claim 1, wherein said step of filtering said images uses two neighborhoods (N1) and (N2), of a given pixel, wherein a gap (GAP) extending between these neighborhoods is user-adjustable.

4. A method of processing images as claimed in claim 3, wherein a height (H) and a length (L) of said neighborhoods are adjustable.

5. A method of processing images as claimed in claim 1, wherein said step of analyzing the connectivity of neighboring pixels uses a neighborhood of a given pixel, which neighborhood extends in the direction of the pixel considered and, determined during the step of estimating.

6. A method of processing images as claimed in claim 5, wherein the length of said neighborhood is adjustable.

7. A method of processing images as claimed in claim 1, wherein the step of selecting groups of pixels uses an adjustable parameter M, which parameter M allows computation of a minimal sum of contrasts of the pixels of a given group required for the group to be selected.

8. A method of processing images as claimed in claim 1, further including:

skeletonizing said images to extract a skeleton of curvilinear structures,

measuring diameters of arteries found in said skeletonized images,

detecting arterial anomalies on the basis of the basis of the diameters and predefined rules.

9. A computer readable medium comprising a set of computer readable instructions;

which computer readable instruction may be processed by a computer to implement a method of processing images as claimed in claim 1.

10. An image-processing system comprising a programable computer programmed with a set of instructions for carrying out the method as set forth in claim 1, including a device for projecting images processed thereby, and a device for storing said images.

11. A method of processing images, comprising the steps of:

acquiring at least a first digitized image and a second digitized image of an artery to be analyzed for artery anomalies,

filtering said first and second digitized images;

selecting pixels within said filtered, digitized images pertaining to a curvilinear structure, and

estimating a direction of each selected pixel and analyzing a connectivity of neighboring pixels based on the estimated direction for each selected pixel, and

selecting groups of pixels as a function of the result of said analyzing,

skeletonizing the first and the second processed images to extract a first skeleton of the curvilinear structure of the first processed image, and a second skeleton of the curvilinear structure of the second processed image,

reconstructing a 3D image of the artery, based on the first snd the second processed image and skeletons,

measuring artery diameters, within the reconstructed 3D image of the artery, and

determining the existence of artery anomalies based on said diameters and rules.