IP Library Granted Patent US 7,715,605
Granted Patent B2
US 7,715,605 · App. 11/507,383 · Granted May 11, 2010

Systems and methods for computer aided detection of spinal curvature using images and angle measurements

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Quick Facts
Patent No.
US 7,715,605
App. No.
11/507,383
Granted
May 11, 2010
Kind
B2
Abstract

A method for providing automatic detection of curvature of a spine and computation of specific angles in images of the spine includes automatically displaying the curvature of the spine as a line in an image of the spine, and computing at least one of a first angle or a second angle based on the line of the curvature of the spine.

Claims (90)

1. A method, comprising:

automatically displaying curvature of a spine as a line in an image of the spine; wherein automatically displaying the curvature of the spine comprises:

improving contrast of the image of the spine by generating a mask of the spine and improving the contrast of vertebrae of the spine, wherein generating a mask of the spine comprises finding a region of interest, wherein finding a region of interest comprises:

dividing the image into a plurality of slices, wherein a width of each slice is equal to a width of the image; and a height of each slice is a predetermined number of times smaller than a height of the image;

for each slice, equalizing a histogram to spread the intensity distribution and applying a threshold of a predetermined percentage of a maximum intensity to raise the contrast;

shifting each of the slices by one tenth of the height of the slice;

repeating the steps of dividing, equalizing and shifting a predetermined number of times, obtaining a set of results; and

calculating a mean of the set of results.

2. The method of claim 1 , further comprising:

computing at least one of a first angle or a second angle based on the line of the curvature of the spine, wherein the first angle is a Cobb angle and the second angle is a kyphotic angle.

3. The method of claim 1 , further comprising automatically detecting whether the image is a first view or a second view of the spine.

4. The method of claim 3 , wherein the first view is lateral view of the spine and the second view is a coronal image of the spine.

5. The method of claim 1 , wherein automatically displaying the curvature of the spine as a line in the image of the-spine further comprises:

isolating the spine in the image;

detecting boundaries of the spine from the improved image; and

displaying a middle line in the spine that represents the curvature of the spine in the image.

6. The method of claim 5 , wherein the image is a first view of the spine, and wherein isolating the spine in the first view of the spine comprises:

determining a top cut point, the top cut point corresponding to the beginning of the spine; and

determining a bottom cut point, the bottom cut point corresponding to the bottom of the spine.

7. The method of claim 6 , wherein determining the top cut point comprises detecting a head in the first view of the image.

8. The method of claim 7 , wherein detecting the head in the first view of the image comprises equalizing a histogram, thresholding and segmenting the head.

9. The method of claim 6 , wherein determining the bottom cut point comprises detecting a pelvis in the first view of the image.

10. The method of claim 6 , wherein the first view of the image is one of a lateral view of the spine or a coronal view of the spine.

11. The method of claim 6 , further comprising removing a portion of each side of the image.

12. The method of claim 5 , wherein generating a mask of the spine further comprises generating a mask to enable removal of artifacts.

13. The method of claim 12 , wherein, when the image is a coronal view of the spine, generating the mask comprises:

generating a binary representation of the image;

applying a morphological closing to fill gaps with a small round structuring element in the binary representation of the image; and

doing a region labeling and selecting a region of interest in the binary representation of the image.

14. The method of claim 13 , further comprising applying constraints in the width of the mask to improve the mask.

15. The method of claim 12 , wherein, when the image is a lateral view of the spine, generating the mask comprises:

generating a binary representation of the image;

doing a region labeling and selecting a region of interest in the binary representation of the image;

separately extracting a right boundary and a left boundary of the region as vectors;

selecting the smoothest curve; and

drawing a mask following the curve and adding a predetermined value representing a width of the spine.

16. The method of claim 5 , further comprising pre-processing to improve a contrast of the image before isolating the spine in the image.

17. A method, comprising:

automatically displaying curvature of a spine as a line in an image of the spine, wherein automatically displaying the curvature of the spine comprises:

improving contrast of the image of the spine;

detecting boundaries of the spine from the improved image; wherein detecting boundaries of the spine from the improved image comprises:

applying a threshold to the contrast-enhanced image;

doing a region labeling of a binary representation of the contrast-enhanced image and selecting the spine;

along each row of the spine region, storing a minimum and maximum x-coordinates in two right and left vectors: and

smoothing the two vectors with the minimum and maximum x-coordinates using a smoothing window of a predetermined height, wherein the predetermined height is tenth of the image height.

18. The method of claim 5 , wherein displaying a middle line in the spine that represents the curvature of the spine in the X-ray image comprises:

obtaining a middle point for each line of the spine region by computing the middle value between pre-computed left and right vectors; and

joining all the pre computed middle points to form the representation of the curve of the spine.

19. The method of claim 1 , further comprising:

computing a Cobb angle based on the line of the curvature of the spine, wherein computing the Cobb angle based on the curvature of the spine comprises:

determining the global curve of the spine;

finding the maximum positive and negative angles from the curve by calculating an angle at each point of the curve; and

computing the Cobb angle by summing the absolute value of the most negative and positive angles of the curve.

20. The method of claim 19 , wherein calculating an angle at each point of the curve comprises:

computing the angle using a tangent of the curve at the specified point and a horizontal line;

locally applying a Gabor filtering along the direction set by the computed angle;

estimating an orientation from endplates of the vertebrae based on the Gabor filtering; and

setting the orientation as the Cobb angle.

21. The method of claim 1 , further comprising:

computing a kyphotic angle based on the line of the curvature of the spine, wherein computing the kyphotic angle based on the curvature of the spine comprises:

determining a global curve of the spine;

finding the maximum positive and negative angles from the curve by calculating an angle at each point of the curve; and

computing the kyphotic angle by summing the absolute value of the most negative and positive angles of the curve.

22. The method of claim 21 , wherein calculating an angle at each point of the curve comprises:

computing the angle using a tangent of the curve at the specified point and a horizontal line;

locally applying a Gabor filtering along the direction set by the computed angle;

estimating an orientation from endplates of the vertebrae based on the Gabor filtering; and

setting the orientation as the kyphotic angle.

23. A system comprising:

a memory device for storing a program;

a processor in communication with the memory device, the processor operative with the program to:

automatically display curvature of a spine as a line in an image of the spine;

divide the image into a plurality of slices, wherein a width of each slice is equal to a width of the image, and wherein a height of each slice is a predetermined number of times smaller than a height of the image;

for each slice, equalize a histogram to spread the intensity distribution and apply a threshold of a predetermined percentage of a maximum intensity to raise the contrast;

shift each of the slices by one tenth of the height of the part;

repeat the steps of dividing, equalizing and shifting a predetermined number of times to obtain a set of results; and

calculate a mean of the set of results.

24. The system of claim 23 , wherein the processor is further operative with the program to:

isolate the spine in the image;

improve the contrast of the image of the spine;

detect boundaries of the spine from the improved image; and

display a middle line in the spine that represents the curvature of the spine in the image.

25. The system of claim 23 , wherein the processor is further operative with the program to automatically detect whether the image is a lateral view of the spine or a coronal image of the spine.

26. The system of claim 23 , wherein the processor is further operative with the program to:

generate a binary representation of the image;

do a region labeling and select a region of interest in the binary representation of the image;

separately extract a right boundary and a left boundary of the region as vectors; select the smoothest curve; and

draw a mask following the curve and add a predetermined value representing a width of the spine.

27. The system of claim 23 , wherein the processor is further operative with the program to:

compute at least one of a first angle or a second angle based on the line of the curvature of the spine.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 17, 2007
From: SIEMENS CORPORATE RESEARCH, INC.
To: SIEMENS MEDICAL SOLUTIONS USA, INC.
Reel/Frame 019309/0669 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 6, 2006
From: VERRE, JEANNE; NOVAK, CAROL L.; ODRY, BENJAMIN; REISMAN, JAMES G.
To: SIEMENS CORPORATE RESEARCH, INC.
Reel/Frame 018358/0245 →