System and method for displaying images on a PACS workstation based on level of significance

• US 7,738,684 B2
• Filed: 01/18/2006
• Issued: 06/15/2010
• Est. Priority Date: 11/24/2004
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Mahesh, Prakash, Morita, Mark M., Kariathungal, Murali Kumaran
• Primary Examiner(s): Ahmed; Samir A
• Assistant Examiner(s): RASHIDIAN, MOHAMMAD M
• Application Number:
  US11/334,123
• Publication Number:
  US 20060139318A1
• Time in Patent Office: 1,609 Days
• Field of Search: 382128-132, 382/254, 382/294, 382/173, 382/204, 382/100, 378/16, 378/98.9, 378/4, 378/8, 378/901, 378/63, 358/518, 345/156, 345/424, 345/552, 345/581, 345/629, 600/411, 600/407, 600/437, 600/300, 703/3, 707/10
• US Class Current: 382/128
• CPC Class Codes: A61B 2017/00216 with eye tracking or head position tracking control
• CPC Class Codes: G06F 3/013 Eye tracking input arrangements G06F3/015 takes precedence
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Certain embodiments of the present invention provide methods and systems for determine a level of significance of an image. Certain embodiments include selecting one or more parameters for use in determining a level of significance for an image, assigning a value to each of the one or more parameters, and determining the level of significance for the image based on the parameters and the values associated with each of the one or more parameters. One or more parameters may be weighted to affect determination of the level of significance. An offset may be added to the determination of the level of significance for the image. Parameters may include clinical relevance, diagnosis pattern, segmented area, number of pixels, and/or reading time for the image, for example.

Claims

1. A computer-implemented method for determining a level of significance for an image among a plurality of images in a study, said method comprising:

selecting one or more parameters for use in determining a level of significance for a plurality of images in a study, wherein said one or more parameters include clinical relevance, segmented area, and reading time for each image in said plurality of images to determine said level of significance;

assigning a value to each of said one or more parameters;

determining, using a processor, said level of significance for each image in relation to said plurality of images in the study based on said parameters and said value associated with each of said one or more parameters; and

outputting, using a processor, the plurality of images for viewing in an order determined based on said level of significance for each image.

2. The method of claim 1, further comprising assigning a weight at least one of said one or more parameters to affect determination of said level of significance.

3. The method of claim 1, further comprising adding an offset to said determination of said level of significance for said image.

4. The method of claim 1, wherein said one or more parameters further include at least one of diagnosis pattern, and number of pixels for said image.

5. The method of claim 1, wherein said level of significance is stored in association with said image.

6. The method of claim 1, wherein said level of significance is determined using an equation:

level of significance=a*(clinical relevance)+b* (segmented area)+c*(reading time)+d, wherein a, b and c are coefficients and d is an offset.

7. The method of claim 1, wherein said level of significance is automatically determined when a user marks said image as significant.

8. The method of claim 1, further comprising arranging said image on a display based on said level of significance.

9. A non-transitory computer-readable storage medium including a set of instructions for execution on a computer, the set of instructions comprising:

a parameter selection routine for selecting one or more parameters for use in determining a level of significance for an image among a plurality of images in a study, said parameter selection routine assigning a value to each of said one or more parameters for said image wherein said one or more parameters include clinical relevance, segmented area, and reading time for each image in said plurality of images to determine said level of significance;

a significance determination routine for generating said level of significance for said image in relation to said plurality of images in the study based on said parameters and said value associated with each of said one or more parameters; and

an output routine for outputting the plurality of images for viewing in an order determined based on said level of significance for each image.

10. The tangible computer-readable storage medium of claim 9, wherein said significance determination routine assigns a weight at least one of said one or more parameters to affect generation of said level of significance.

11. The tangible computer-readable storage medium of claim 9, wherein said parameter selection routine adds an offset for using in determining said level of significance for said image.

12. The tangible computer-readable storage medium of claim 9, wherein said one or more parameters further include at least one of diagnosis pattern, and number of pixels, for said image.

13. The tangible computer-readable storage medium of claim 9, wherein said level of significance is generated using an equation:

level of significance=a * (clinical relevance)+b * (segmented area)+c * (reading time)+d, wherein a, b and c are coefficients and d is an offset.

14. A system for determining a level of significance for an image, said system comprising:

a processor coupled to a memory, wherein the processor is programmed to provide;

a parameter configuration module for gathering information regarding one or more parameters for computation of a level of significance for an image among a plurality of images in a study, each of said one or more parameters having a value,

wherein said one or more parameters include clinical relevance, segmented area, and reading time for each image in said plurality of images to determine said level of significance;

a significance module for calculating a level of significance for said image in relation to said plurality of images in the study based at least in part on a combination of said one or more parameters; and

an output module for outputting the plurality of images for viewing in an order determined based on said level of significance for each image.

15. The system of claim 14, wherein said level of significance for said image is stored as meta-data associated with said image.

16. The system of claim 14, further comprising a data store including level of significance image information.

17. The system of claim 14, wherein said level of significance is generated using an equation:

level of significance=a * (clinical relevance)+b * (segmented area)+c * (reading time)+d, wherein a, b and c are coefficients and d is an offset.

18. The system of claim 14, wherein said one or more parameters further include at least one of diagnosis pattern, and number of pixels for said image.

19. The system of claim 14, wherein said significance module assigns a weight at least one of said one or more parameters to affect generation of said level of significance.