SYSTEMS AND METHODS FOR IDENTIFYING BONE MARROW IN MEDICAL IMAGES

• US 20110158494A1
• Filed: 12/30/2009
• Published: 06/30/2011
• Est. Priority Date: 12/30/2009
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Bar-Shalev, Avi, Manjeshwar, Ravindra Mohan
• Granted Patent: US 9,058,665 B2
• Time in Patent Office: Days
• US Class Current: 382/131
• CPC Class Codes: A61B 6/032 Transmission computed tomography [CT]
• CPC Class Codes: A61B 6/505 for diagnosis of bone
• CPC Class Codes: A61B 6/508 for non-human patients
• CPC Class Codes: A61B 6/5241 combining overlapping images of the same imaging modality, e.g. by stitching
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/20164 Salient point detection; Corner detection
• CPC Class Codes: G06T 2207/30008 Bone
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/13 Edge detection
• CPC Class Codes: G06T 7/187 involving region growing; involving region merging; involving connected component labelling

Abstract

Systems and method for identifying bone marrow in medical images are provided. A method includes obtaining a three-dimensional (3D) computed tomography (CT) volume data set corresponding to an imaged volume and identifying voxels in the 3D CT volume data set having a Hounsfield Unit (HU) value below a bone threshold. The voxels are identified without using image continuity. The method further includes marking the identified voxels as non-bone voxels, determining definite tissue voxels based on the identified non-bone voxels and expanding a region defined by the definite tissue voxels. The method also includes segmenting the expanded region to identify bone voxels and bone marrow voxels and identifying bone marrow as voxels that are not the bone voxels.

Claims

1. A method for identifying bone marrow in medical image data, the method comprising:

obtaining a three-dimensional (3D) computed tomography (CT) volume data set corresponding to an imaged volume;

identifying voxels in the 3D CT volume data set having a Hounsfield Unit (HU) value below a bone threshold, the voxels identified without using image continuity;

marking the identified voxels as non-bone voxels;

determining definite tissue voxels based on the identified non-bone voxels;

expanding a region defined by the definite tissue voxels;

segmenting the expanded region to identify bone voxels and bone marrow voxels; and

identifying bone marrow as voxels that are not the bone voxels.

2. A method in accordance with claim 1 wherein the expanding comprises adding at least one layer of voxels to the determine definite tissue voxels.

3. A method in accordance with claim 1 further comprising displaying an image of a 3D CT volume generated from the 3D CT volume data set and highlighting the voxels corresponding to the identified bone marrow.

4. A method in accordance with claim 1 further comprising dividing the voxels identified as bone marrow into red bone marrow and yellow bone marrow using corresponding red bone marrow HU values and yellow bone marrow HU values.

5. A method in accordance with claim 1 further comprising selecting as an initial voxel for the determining definite tissue voxels a non-bone voxel.

6. A method in accordance with claim 5 wherein the initial voxel is a corner voxel in the 3D CT volume data.

7. A method in accordance with claim 1 further comprising acquiring a full body CT scan of a patient to obtain the 3D CT volume data set.

8. A method in accordance with claim 1 further comprising determining a total mass of bone marrow based on the voxels corresponding to the identified bone marrow voxels.

9. A method in accordance with claim 1 wherein the bone threshold is 200 Hounsfield Units (HU).

10. A method in accordance with claim 1 wherein the bone threshold is determined based on an HU value for hard bone.

11. A method in accordance with claim 1 further comprising counting a number of neighbor tissue voxels for each identified non-bone voxel.

12. A method in accordance with claim 11 wherein determining definite tissue voxels comprises identifying definite tissue voxels as voxels surrounded by only tissue voxels and connected to an initial voxel that is a non-bone voxel.

13. A method for identifying bone marrow in medical images, the method comprising:

identifying bone regions in a three-dimensional (3D) image based on a bone threshold value;

segmenting non-bone regions from the 3D image having the identified bone regions, wherein boundaries for the segmenting are determined from the identified bone regions; and

identifying bone marrow regions in the 3D image as regions not identified as bone regions or segmented as non-bone regions.

14. A method in accordance with claim 13 wherein segmenting the non-bone regions comprises identifying air and soft tissue regions of the 3D image.

15. A method in accordance with claim 13 further comprising using image continuity limited by the boundaries to segment the non-bone regions.

16. A method in accordance with claim 13 wherein identifying the bone regions is non-bounded and performed without image continuity.

17. A method in accordance with claim 13 wherein identifying the bone regions comprises identifying voxels in the 3D image corresponding to hard bones.

18. A method in accordance with claim 13 wherein the segmenting comprises applying a morphological filling on a thresholded 3D image formed from identifying the bone regions.

19. A method in accordance with claim 18 further comprising subtracting the thresholded 3D image from a filled 3D image formed from applying the morphological filling.

20. A method in accordance with claim 19 wherein the 3D image comprises voxels each having a corresponding Hounsfield Unit (HU) value and further comprising resetting negative HU values to zero.

21. A method in accordance with claim 13 wherein the 3D image comprises voxels each having a corresponding Hounsfield Unit (HU) value and further comprising dividing the identified bone marrow regions into red marrow regions and yellow marrow regions based on the HU value of the corresponding voxels.

22. A computed tomography (CT) imaging system comprising:

a gantry supporting an x-ray source and a detector array for rotatable operation to scan a patient to acquire a three-dimensional (3D) image data set;

an image reconstructor configured to reconstruct a 3D image of the patient using the 3D image data set; and

a bone marrow segmentation module configured to automatically segment bone marrow in the reconstructed 3D image.

23. A CT imaging system in accordance with claim 22 wherein the bone marrow segmentation module is configured to automatically segment bone marrow by:

identifying bone regions in the 3D image based on a bone threshold value;

segmenting non-bone regions from the 3D image having the identified bone regions, wherein boundaries for the segmenting are determined from the identified bone regions; and

identifying bone marrow regions in the 3D image as regions not identified as bone regions or segmented as non-bone regions.