System and method for automatic detection and measurement of malacia in the airways

• US 8,195,269 B2
• Filed: 07/02/2007
• Issued: 06/05/2012
• Est. Priority Date: 07/07/2006
• Status: Active Grant

• Current Assignee: Siemens Healthcare GMBH (Siemens AG)
• Original Assignee: Siemens Medical Solutions USA Incorporated (Siemens AG)
• Inventors: Bogoni, Luca, Valadez, Gerardo Hermosillo
• Primary Examiner(s): Casler, Brian
• Assistant Examiner(s): HUYNH, PHONG KY
• Application Number:
  US11/772,379
• Publication Number:
  US 20080009683A1
• Time in Patent Office: 1,800 Days
• Field of Search: 600/407, 600/529, 600/533, 382/128, 382/131, 382/294
• US Class Current: 600/407
• CPC Class Codes: A61B 5/085 Measuring impedance of respiratory organs or lung elasticity
• CPC Class Codes: A61B 6/5217 extracting a diagnostic or physiological parameter from medical diagnostic data
• CPC Class Codes: G06T 2207/10072 Tomographic images
• CPC Class Codes: G06T 2207/30061 Lung
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/33 using feature-based methods
• CPC Class Codes: G06T 7/38 Registration of image sequences
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

A method of detecting malacia in airways includes providing a plurality of 3-dimensional (3D) digital lung images acquired over an inhalation/exhalation cycle from a same subject, each said image comprising a set of intensities on a 3-dimensional grid of points, registering a successive pair of images, wherein a registration mapping of the point grid of one image is calculated, locating airways in each of said pair of images, and collecting those points between the airways in each of said pair of images, wherein a volume of said collected points is a measure of an extent of malacia in said airways.

Claims

1. A method of detecting malacia in airways, comprising the steps of:

receiving, by a computer system, a plurality of 3-dimensional (3D) digital lung images acquired over an inhalation/exhalation cycle from a same subject, each said image comprising a set of intensities on a 3-dimensional grid of points;

registering, by the computer system, a successive pair of images, wherein a registration mapping of the point grid of one image is calculated;

calculating, by the computer system, a quality factor of said registration mapping, wherein the quality factor is indicative of rigidity of the registration mapping;

locating, by the computer system, airways in each of said pair of images; and

if the quality factor indicates that the registration mapping is sufficiently rigid, collecting, by the computer system, points between volumes of the airways in each of said pair of images, wherein the points are used to obtain a volume difference that is a measure of an extent of malacia in said airways;

wherein if said quality factor is greater than a predetermined threshold, accepting the registration, otherwise repeating said steps of registering the pair of images and calculating a quality factor until the quality factor exceeds the predetermined threshold;

wherein said quality factor Q is defined as

2. The method of claim 1, wherein said registration mapping is a non-rigid registration mapping φ

that changes spatial coordinates corresponding to said point grid

3. The method of claim 2, wherein said registration mapping is locally rigid.

4. The method of claim 2, wherein a determinant |Dφ

|(x,y,z) of a Jacobian matrix Dφ

of said registration mapping,

5. The method of claim 1, wherein the α

₁ and α

₂ are

6. The method of claim 5, wherein A=B=10, E₁=4 and E₂=8.

7. The method of claim 1, wherein the plurality of acquired 3D digital lung images comprises a time series of images, and the method further comprising registering each successive pair of images in said time series of images, and for each pair with an acceptable registration mapping, growing a volume between the airways in each of said pair of images, and accumulating said volumes over all pairs of successive images.

8. A method of detecting malacia in airways, comprising the steps of:

providing a pair of 3-dimensional (3D) digital lung images, each said image comprising a set of intensities on a 3-dimensional grid of points;

registering a successive pair of images by calculating a locally rigid registration mapping φ

that changes spatial coordinates corresponding to said point grid from one image (x,y,z) to the other (X,Y,Z) defined by

9. The method of claim 8, further comprising providing a plurality of 3-dimensional (3D) digital lung images acquired over an inhalation/exhalation cycle from a same subject and registering each successive pair of images.

10. The method of claim 9, further comprising segmenting airways in each of said pair of images, and growing a volume between the airways in each of said pair of images, wherein said volume difference is a measure of an extent of malacia in said airways.

11. A non-transitory program storage device readable by a computer, tangibly embodying a program of instructions executable by the computer to perform the method steps for detecting malacia in airways, said method comprising the steps of

receiving a plurality of 3-dimensional (3D) digital lung images acquired over an inhalation/exhalation cycle from a same subject, each said image comprising a set of intensities on a 3-dimensional grid of points;

registering a successive pair of images, wherein a registration mapping of the point grid of one image is calculated;

calculating a quality factor of said registration mapping, wherein the quality factor is indicative of rigidity of the registration mapping;

locating airways in each of said pair of images; and

if the quality factor indicates that the registration mapping is sufficiently rigid, collecting points between volumes of the airways in each of said pair of images, wherein the points are used to obtain a volume difference that is a measure of an extent of malacia in said airways;

wherein if said quality factor is greater than a predetermined threshold, accepting the registration, otherwise repeating said steps of registering the pair of images and calculating a quality factor until the quality factor exceeds the predetermined threshold

wherein said quality factor Q is defined as

12. The computer readable program storage device of claim 11, wherein said registration mapping is a non-rigid registration mapping φ

that changes spatial coordinates corresponding to said point grid

13. The computer readable program storage device of claim 12, wherein said registration mapping is locally rigid.

14. The computer readable program storage device of claim 12, wherein a determinant |Dφ

|(x,y,z) of a Jacobian matrix Dφ

of said registration mapping,

15. The computer readable program storage device of claim 11, wherein the α

₁ and α

₂ are

16. The computer readable program storage device of claim 15, wherein A=B=10, E₁=4 and E₂=8.

17. The computer readable program storage device of claim 11, wherein the plurality of acquired 3D digital lung images comprises a time series of images, and the method further comprising registering each successive pair of images in said time series of images, and for each pair with an acceptable registration mapping, growing a volume between the airways in each of said pair of images, and accumulating said volumes over all pairs of successive images.