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

• US 5,799,099 A
• Filed: 06/06/1995
• Issued: 08/25/1998
• 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): Couso, Yon J.
• Assistant Examiner(s): NGUYEN, HA T
• Application Number:
  US08/471,456
• Time in Patent Office: 1,176 Days
• Field of Search: 382/288, 382/291, 382/154, 382/131, 382/201, 382/170, 382/308, 382/260, 382/262, 382/254, 128/653.1, 128/653.2, 128/653.4, 364/413.13, 364/413.14, 364/413.15, 378/162-164, 378/204, 378/205, 600/426, 600/425
• US Class Current: 382/131
• 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 method for automatically localizing a predetermined number M of fiducial markers in at least one image volume, comprising steps of:

searching the at least one image volume for candidate markers, said markers including a number of three-dimensional connected voxels having similar intensities and being within a predetermined size range;

representing each of said candidate markers by a candidate voxel containing the centroid of the candidate marker; and

examining a three-dimensional region in the at least one image volume around each of the candidate voxels and determining which of said candidate markers represented by said candidate voxels most likely correspond to said fiducial markers in said at least one image volume, and including for each of said candidate voxels;

determining whether a size and shape of a set of foreground voxels connected to said candidate voxel is similar to a foreground component of a fiducial marker;

discarding the candidate voxel if the size and shape are not determined to be similar;

determining a centroid of the set of foreground voxels;

repeating said determining steps until a same centroid has been determined twice in succession;

discarding the candidate voxel if the determining steps are implemented a predetermined number of times; and

if a same centroid has been determined twice in succession, recording said same centroid as a final centroid and recording a corresponding intensity of said final centroid.

2. The method of claim 1, wherein said predetermined number of times is three.

3. The method of claim 1, further comprising a step of ranking the recorded final centroids of each of said candidate voxels according to their corresponding recorded intensities.

4. A method for automatically localizing three-dimensional centroids of a predetermined number M of fiducial markers in at least one image volume, comprising steps of:

searching the at least one image volume for candidate markers, said candidate markers including a number of three-dimensional connected voxels having similar intensities and being within a predetermined size range and representing each of said candidate markers by a candidate voxel containing the centroid of the candidate marker, including;

applying a median filter within each of a plurality of slices of the at least one image volume;

forming a new smaller image volume for each slice by subsampling;

determining an intensity threshold value;

producing a binary image from said new smaller image of foreground and background voxels in response to said intensity threshold value;

filling in any holes in the binary image;

removing small components and small protrusions on large components appearing in the binary image;

selecting components in the removed binary image which are most similar to a fiducial marker, said number of components being larger than said predetermined number M; and

providing said selected components as the candidate voxels;

examining a three-dimensional region in the at least one image volume around each of the candidate voxels and determining which of said candidate markers represented by said candidate voxels most likely correspond to said fiducial markers in said at least one image volume including for each of said candidate voxels;

determining whether a size and shape of a set of foreground voxels connected to said candidate voxel is similar to a foreground component of a marker;

discarding the candidate voxel if the size and shape are not determined to be similar;

determining a centroid of the set of foreground voxels;

repeating said determining steps until a same centroid has been determined twice in succession;

discarding the candidate voxel if the determining steps are implemented a predetermined number of times; and

if a same centroid has been determined twice in succession, recording said same centroid as a final centroid and recording a corresponding intensity of said final centroid.

5. The method of claim 4, wherein said predetermined number of times is three.

6. The method of claim 4, further comprising a step of ranking the recorded final centroids of each of said candidate voxels according to their corresponding recorded intensities.