Marker identification and processing in x-ray images
A mechanism for rapidly detecting and localizing external markers placed on a patient in projection images. Embodiments of the invention allow the markers to be detected even in the presence of dense surrounding anatomy and extensive patient motion. Once the positions of the marker points on the projection images are extracted, the marker points can be used to perform marker-based patient motion detection. Embodiments of the invention can also be used outside of motion correction, such as for scanner calibration, automatic cephalometric measurements, and quality control assessment.
1. A method for identifying marker associated points in an image, the method executed by an imaging system including a scanner, a computer with an electronic processing unit, and a memory module storing a marker point identification module executable by the electronic processing unit, the method comprising:
obtaining, at the computer, an image based on image data generated by the scanner;
applying, with the electronic processing unit, a two-dimensional high-pass filter with x-ray compensation to the image to suppress background and, thereby, create a background suppressed image; and
extracting, with the electronic processing unit, marker associated points from the background suppressed image.
2. The method of claim 1 , further comprising applying a two-dimensional low-pass filter to the image to create a low-pass image, and wherein applying the two-dimensional high-pass filter includes combining the image with the low-pass image.
3. The method of claim 1 , wherein applying the two-dimensional high-pass filter includes sequentially applying two or more one-dimensional high-pass filters to the image, each performed in a different two-dimensional direction on the image.
4. The method of claim 3 , wherein applying each one-dimensional high-pass filter includes combining at least one of
a one-dimensional low-pass filtered representation of the image with the image, and
a one-dimensional low-pass filtered representation of a temporary image from an earlier application of the one-dimensional high-pass filter with the temporary image.
5. The method of claim 4 , wherein the one-dimensional low-pass filtered representation of the image is created by applying cumulative mean filtering, the filtering comprising:
creating, using the electronic processing unit, a cumulative image from the image, wherein each pixel of the cumulative image represents a cumulative sum of lower pixels in a direction of the filter;
shifting, with the electronic processing unit, the cumulative image by a filtering factor to create a shifted image;
subtracting, with the electronic processing unit, the cumulative image from the shifted image to create a difference image;
dividing, with the electronic processing unit, the difference image by the filtering factor.
6. The method of claim 3 , wherein combining the image and the one-dimensional low-pass filtered representation of the image accounts for non-linear attenuation of x-rays and includes a pixel-by-pixel division of the image by the one-dimensional low-pass filtered representation of the image.
7. The method of claim 6 , wherein the pixel-by-pixel division is performed using pixels of the one-dimensional low-pass filtered representation of the image as a numerator.
8. The method of claim 3 , wherein combining the image and the one-dimensional low-pass filtered representation of the image includes subtraction.
9. The method of claim 1 , wherein extracting the marker associated points from the background suppressed image includes defining local maxima in the background suppressed image.
10. The method of claim 9 , wherein defining the local maxima in the background suppressed image includes identifying pixels in the background suppressed image that have eight neighboring pixels with smaller pixel values.
11. The method of claim 9 , wherein extracting the marker associated points from the background suppressed image further includes growing candidate regions based on the local maxima.
12. The method of claim 11 , wherein extracting the marker associated points from the background suppressed image further includes applying shape criterion to each candidate region.
13. The method of claim 12 , wherein applying the shape criterion to each candidate region includes determining a ratio of a pixel area of each candidate region and an area defined by a mean radius of each candidate region squared times pi.
14. The method of claim 11 , wherein extracting the marker associated points from the background suppressed image further includes eliminating candidate regions by comparing candidate regions in adjacent projection images and applying nearness criteria between candidate regions.
15. An imaging system including a scanner, a computer with an electronic processing unit, and a memory module storing a marker point identification module executable by the electronic processing unit, wherein the marker point identification module, when executed, is configured to:
obtain, at the computer, an image based on image data generated by the scanner;
apply a two-dimensional high-pass filter with x-ray compensation to the image to suppress background and, thereby, create a background suppressed image; and
extract marker associated points from the background suppressed image.
16. The imaging system of claim 15 , wherein the marker point identification module, when executed, is further configured to
apply a two-dimensional low-pass filter to the image to create a low-pass image, and
apply the two-dimensional high-pass filter by combining the image with the low-pass image.
17. The imaging system of claim 15 , wherein the marker point identification module, when executed, is further configured to apply the two-dimensional high-pass filter by sequentially applying two or more one-dimensional high-pass filters to the image, each performed in a different two-dimensional direction on the image.
18. The imaging system of claim 15 , wherein the marker point identification module, when executed, is further configured to extract the marker associated points from the background suppressed image by defining local maxima in the background suppressed image, wherein defining local maxima includes identifying pixels in the background suppressed image that have eight neighboring pixels with smaller pixel values.
19. The imaging system of claim 18 , wherein the marker point identification module, when executed, is further configured to extract the marker associated points from the background suppressed image by
growing candidate regions based on the local maxima,
applying shape criterion to each candidate region, and
eliminating candidate regions by comparing candidate regions in adjacent projection images and applying nearness criteria between candidate regions.