HISTOGRAM TILE MAP FOR GPU BASED HISTOGRAM COMPUTATION

• US 20080112614A1
• Filed: 06/06/2007
• Published: 05/15/2008
• Est. Priority Date: 11/14/2006
• Status: Abandoned Application

• Current Assignee: Siemens Medical Solutions USA Incorporated (Siemens AG)
• Original Assignee: Siemens Corporate Research Incorporated (Siemens AG)
• Inventors: Aharon, Shmuel, Fluck, Oliver
• Application Number:
  US11/758,806
• Publication Number:
  US 20080112614A1
• Time in Patent Office: Days
• US Class Current: 382/168
• CPC Class Codes: G06V 10/25 Determination of region of interest [ROI] or a volume of interest [VOI]
• CPC Class Codes: G06V 10/50 by performing operations within image blocks; by using histograms, e.g. histogram of oriented gradients [HoG]; by summing image-intensity values; Projection analysis
• CPC Class Codes: G06V 2201/03 Recognition of patterns in medical or anatomical images

Abstract

A method for identifying a region of interest within an image includes receiving an image. The image is divided into a plurality of tiles. It is determined which of the plurality of tiles includes the region of interest. A graphics processing unit (GPU) calculates a pixel intensity histogram for tiles that have been determined to include the region of interest. The region of interest is identified based on the calculated pixel intensity histograms.

Claims

1. A method for identifying a region of interest within an image, comprising:

receiving an image;

dividing the image into a plurality of tiles;

determining which of the plurality of tiles include the region of interest;

calculating, within a graphics processing unit (GPU), a pixel intensity histogram for tiles that have been determined to include the region of interest and not calculating a pixel intensity histogram for tiles that do not include the region of interest; and

identifying the region of interest based on the calculated pixel intensity histograms.

2. The method of claim 1, wherein each of the plurality of tiles is an equally sized region of the image.

3. The method of claim 1, wherein determining which of the plurality of tiles includes the region of interest comprises performing a reduce operation.

4. The method of claim 3, wherein the reduce operation is performed one or more times upon the image or a processed version of the image.

5. The method of claim 1, wherein determining which of the plurality of tiles includes the region of interest is initially based on user input.

6. The method of claim 1, wherein two or more of the pixel intensity histograms for each tile are performed, in parallel, within the GPU.

7. The method of claim 1, wherein the received image is stored as a texture in the texture memory of the GPU.

8. The method of claim 1, wherein identifying the region of interest based on the calculated pixel intensity histograms comprises calculating a global image histogram based on the calculated pixel intensity histograms.

9. The method of claim 1, wherein identifying the region of interest based on the calculated pixel intensity histograms comprises:

receiving an initial segmentation based on a user input; and

iteratively improving the calculated region of interest.

10. The method of claim 9, wherein the iterative improvement comprises:

refining the determination as to which of the plurality of tiles includes the region of interest;

recalculating the pixel intensity histogram for each tile that has been determined to include the region of interest; and

identifying an improved region of interest based on the recalculated pixel intensity histograms.

11. The method of claim 1, further comprising locating the identified region of interest on the image.

12. A system for identifying a region of interest within an image, comprising:

a graphical processing unit (GPU) for storing the image in texture memory;

an image subdividing unit for dividing the image into a plurality of tiles of the same size;

a tile map for indicating which of the plurality of tiles are excluded from calculation; and

a tile histogram calculating unit for calculating tile histograms for each of the plurality of tiles that are not excluded from calculation and not calculating tile histograms for each of the plurality of tiles that are excluded from calculation.

13. The system of claim 12, further comprising an image acquisition system for providing the image to the GPU.

14. The system of claim 13, wherein the image acquisition system is a medical imaging device.

15. The system of claim 13, wherein the image acquisition system is a medical image database system.

16. A computer system comprising:

a processor; and

a program storage device readable by the computer system, embodying a program of instructions executable by the processor to perform method steps for calculating a global pixel intensity histogram, the method comprising;

dividing an image into a plurality of tiles;

generating a tile map for indicating which of the plurality of tiles are excluded from calculation;

calculating, within a graphics processing unit (GPU), a tile histogram for each of the plurality of tiles not excluded from calculation and not calculating a tile histogram for each of the plurality of tiles that are excluded from calculation; and

calculating a global pixel intensity histogram based on the calculated tile histograms.

17. The computer system of claim 16, wherein a region of interest is identified within the image using the tile histograms.

18. The computer system of claim 17, wherein identification of the region of interest using the tile histograms includes image segmentation.

19. The computer system of claim 18, wherein the tile map is generated using user input.

20. The computer system of claim 18, wherein the tile map is generated using a reduce operation.