Automatic technique for localizing externally attached fiducial markers in volume images of the head

• US 5,769,789 A
• Filed: 04/22/1997
• Issued: 06/23/1998
• Est. Priority Date: 02/12/1993
• Status: Expired due to Term

• Current Assignee: Marker
• Original Assignee: George S. Allen
• Inventors: Maurer, Calvin R. Jr., Fitzpatrick, J. Michael, Wang, Matthew Y.
• Primary Examiner(s): Smith, Ruth S.
• Application Number:
  US08/840,533
• Time in Patent Office: 427 Days
• Field of Search: 382/128, 382/131, 382/308, 606/130, 128/653.1, 128/653.2, 128/922, 600/414, 600/426
• US Class Current: 600/414
• CPC Class Codes: A61B 2090/363 Use of fiducial points
• CPC Class Codes: A61B 2090/3916 Bone tissue
• CPC Class Codes: A61B 2090/3987 Applicators for implanting markers
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: A61B 6/12 Arrangements for detecting or locating foreign bodies
• CPC Class Codes: A61B 90/36 Image-producing devices or illumination devices not otherwise provided for
• CPC Class Codes: A61B 90/39 Markers, e.g. radio-opaque or breast lesions markers
• CPC Class Codes: G01R 33/28 Details of apparatus provided for in groups G01R33/44 - G01R33/64
• CPC Class Codes: G06T 2207/10072 Tomographic images
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/10088 Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/30016 Brain
• CPC Class Codes: G06T 2207/30204 Marker
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/155 involving morphological operators
• CPC Class Codes: G06T 7/194 involving foreground-background segmentation
• CPC Class Codes: G06T 7/33 using feature-based methods
• CPC Class Codes: G06T 7/66 of image moments or centre of gravity
• CPC Class Codes: G06T 7/73 using feature-based methods
• CPC Class Codes: G06V 10/25 Determination of region of interest [ROI] or a volume of interest [VOI]

Abstract

An automatic computer implemented technique which may be used for identifying markers and determining the centroids of fiducial markers (e.g., cylindrical fiducial markers) attached to the head in magnetic resonance (MR) and X-ray computed tomography (CT) volume images is disclosed. This technique may be referred to as image space localization. A first portion of the technique identifies many candidate voxel points included in a bright area of the image which may correspond to candidate markers. A second portion of the technique selects from the identified candidate voxels a predetermined number of candidate points of the image volume that are most likely to lie within an actual fiducial marker. The centroid for each of these markers is then determined. The method finds markers whose images are of a higher intensity than their surroundings and which have a given shape and size.

Claims

1. A computer-implemented method for automatically determining candidate fiducial marker voxels in an image volume, the candidate fiducial marker voxels having a predetermined size, the computer-implemented method comprising steps of:

forming a binary image of background and foreground components based on said image volume;

morphologically opening the foreground components of the binary image using an element slightly larger than the predetermined size and morphologically dilating the foreground components using an element consisting of a single voxel; and

locating centroids of components of the binary image on which said morphologically opening and dilating step has been performed and determining the candidate fiducial marker voxels based on said located centroids.

2. The computer-implemented method of claim 1 wherein said image volume includes an image of at least one fiducial marker, the method further comprising a step of:

reviewing a first one of the located centroids by examining a spherical volume centered on said first one of the located centroids that lies within a radius R equal to a largest length of said fiducial marker.

3. The computer-implemented method of claim 2, further comprising a step of:

establishing a brightness threshold t in dependence upon a geometry of the representative fiducial marker.

4. The computer-implemented method of claim 3, further comprising steps of:

searching for the smallest brightness threshold t so that no voxel whose intensity is greater than the brightness threshold t is farther than the radius R from a point of interest, and

if the sum of the volumes of those voxels is less than a first parameter, discarding the point of interest.

5. The computer-implemented method of claim 4, further comprising a step of increasing the brightness threshold t until the volume V of the voxels is less than or equal to a second parameter.

6. The computer-implemented method of claim 5, further comprising a step of locating a center of the determined candidate fiducial marker voxels.

7. The computer-implemented method of claim 1 wherein said image volume includes an image of at least one cylindrical fiducial marker, the method further comprising a step of:

reviewing a first one of the located centroids by examining a spherical volume centered on said first one of the located centroids that lies within a radius R equal to a square root of a sum of squares of a height and a diameter of said cylindrical fiducial marker.

8. A computer-implemented method for determining candidate fiducial marker voxels in an image volume, the candidate fiducial marker voxels having a predetermined size, the computer-implemented method comprising steps of:

forming a binary image of background and foreground components based on said image volume;

performing at least two morphological operations on the foreground components of the binary image using an element slightly larger than said predetermined size to remove small objects, said morphological operations including a morphological opening, a morphological dilation, and a morphological erosion;

locating a centroid of each of the removed small objects and determining candidate fiducial marker voxels based on said located centroid.

9. The computer-implemented method of claim 8 wherein said image volume includes an image of at least one fiducial marker, the method further comprising a step of:

reviewing each located centroid corresponding to the small objects by examining a spherical volume centered on that centroid that lies within a radius R equal to a largest length of said fiducial marker.

10. The computer-implemented method of claim 9, further comprising a step of establishing a brightness threshold in dependence upon a geometry of the representative fiducial marker.

11. The computer-implemented method of claim 10, further comprising steps of:

searching for the smallest brightness threshold t so that no voxel whose intensity is greater than t is farther than the radius R from a point of interest, and

if the sum of the volumes of those voxels is less than a first parameter, discarding the point.

12. The computer-implemented method of claim 11, further comprising a step of increasing t until the volume V of the voxels is less than or equal to a second parameter.

13. The computer-implemented method of claim 12, further comprising a step of locating centers of the determined candidate fiducial marker voxels.

14. The computer-implemented method of claim 8 wherein said image volume includes an image of at least one cylindrical fiducial marker, the method further comprising a step of:

reviewing each located centroid corresponding to the small objects by examining a spherical volume centered on that centroid that lies within a radius R equal to a square root of a sum of squares of a length and a diameter of said cylindrical fiducial marker.