SYSTEMS AND METHODS FOR AUTOMATIC DETECTION AND TESTING OF IMAGES FOR CLINICAL RELEVANCE

• US 20140079303A1
• Filed: 05/04/2011
• Published: 03/20/2014
• Est. Priority Date: 05/04/2011
• Status: Active Grant

• Current Assignee: Stryker European Operations Holdings, LLC (Stryker Corporation)
• Original Assignee: Stryker Trauma GmbH (Stryker Corporation)
• Inventors: Kohnen, Michael, Blau, Arno, Pfrengle, Udo, Epting, Thomas
• Granted Patent: US 9,788,786 B2
• Time in Patent Office: Days
• US Class Current: 382/128
• CPC Class Codes: A61B 5/4869 Determining body composition
• CPC Class Codes: G06T 2207/20004 Adaptive image processing
• CPC Class Codes: G06T 2207/20021 Dividing image into blocks, subimages or windows
• CPC Class Codes: G06T 2207/20224 Image subtraction
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/254 involving subtraction of images

Abstract

Disclosed herein are systems and methods for automatic detection of clinical relevance of images of an anatomical situation. The method includes comparing a first image and a second image and determining whether a difference between the first and second images is at least one of a local type difference and a global type difference. The local type difference is a local difference of the first image and the second image and the global type difference is a global difference between the first image and the second image. The second image is determined as having a clinical relevance if it is determined that the difference between the first image and the second image comprises a local type difference.

Claims

1. A method for automatic detection on clinical relevance of images of an anatomical situation provided by an imaging device, the method comprising:

taking a first image of the anatomical situation;

taking a second image of the anatomical situation;

comparing the first image and the second image and determining a difference between the first image and the second image;

determining whether the difference between the first image and the second image comprises at least one of a local type difference and a global type difference, wherein the local type difference is a local difference of the first image and the second image and wherein the global type difference is a global difference between the first image and the second image, and

determining whether the second image has clinical relevance by determining whether the difference between the first image and the second image comprises a local type difference.

2. The method according to claim 1, further comprising determining the difference of the first image and the second image exceeds a particular threshold.

3. The method according to any one of claim 1, wherein comparing and determining a difference of the first image and the second image includes separating each of the first image and the second image into corresponding image blocks each comprising a plurality of pixels, and comparing at least one of the corresponding image blocks of the first and second image.

4. The method according to claim 3, wherein the local type difference is detected if the difference of an image block of the first image and a corresponding image block of the second image exceeds a first predetermined threshold and wherein the global type difference is detected if the difference of the first image and the second image exceeds a second predetermined threshold, wherein the second threshold is larger than the first threshold.

5. The method according to claim 2, wherein at least one of the threshold and the first threshold is a locally varying threshold.

6. The method according to claim 2, wherein at least one of the threshold, the first threshold and the second threshold is a dynamic threshold.

7. The method according to claim 3, further comprising determining the image block having the maximum local difference and comparing the image block having the maximum local difference with remaining image blocks and determining a local type difference based on the comparison of the image block having the maximum local difference and remaining image blocks.

8. The method according to claim 3, further comprising determining the image block having a significantly increased local difference and comparing the image block having the significantly increased local difference with image blocks in the vicinity of the image block having a significantly increased local difference and determining a local type difference based on the comparison of the image block having the significantly increased local difference with image blocks in the vicinity of the image block having a significantly increased local difference.

9. The method according to any claim 3, further comprising recognizing relevant objects in the first image and determining a local type difference based on a difference of an image block of the first image including the recognized relevant object and a corresponding image block of the second image.

10. The method according to claim 3, wherein comparing and determining a difference of the first image and the second image includes determining an average and a variance of at least a part of corresponding image blocks of the first image and the second image and comparing corresponding image blocks with respect to average and variance.

11. The method according to claim 3, wherein a unique size for all image blocks is dynamically adapted based on a detected size of identified objects of the images.

12. The method according to claim 3, wherein comparing and determining a difference of the first image and the second image includes combining a plurality of image blocks to an image block cluster and comparing corresponding image block clusters.

13. The method according to claim 12, wherein a local type difference is determined if at least one of a difference between an image block of the first image and a corresponding image block of the second image and a difference between an image block cluster of the first image and a corresponding image block cluster of the second image exceeds the first threshold.

14. The method according to claim 1, further comprising detecting a relevant image range, the image range comprising imaged objects, wherein comparing and determining a difference between the first image and the second image is exclusively carried out based on the detected relevant image range.

15. The method according to claim 14, wherein the detected relevant image range is used as base for a following image.

16. The method according to claim 1, further comprising detecting a predetermined characteristic of at least one of the first image and second image, wherein the predetermined characteristic is an indicative for at least one of an imaging device type and imaging device manufacturer.

17. The method according to claim 1, wherein the first image and the second image are generated from a permanent video signal output of an imaging device.

18. A device for automatic detection on clinical relevance of images of an anatomical situation provided by an imaging device, the device comprising:

an image input interface;

a first storage unit for a first image of the anatomical situation taken from the image input interface;

a second storage unit for a second image of the anatomical situation taken from the image input interface;

a comparator unit for comparing and determining a difference between the first image and the second image;

a difference type evaluation unit for evaluating the difference type of the first image and the second image, wherein the difference type evaluation unit is adapted for determining at least one of a local type difference and a global type difference, wherein the local type difference is a local difference of the first image and the second image and wherein the global type difference is a global difference between the first image and the second image; and

an image selection unit for selecting the second image as having a clinical relevance if it is determined that the difference between the first image and the second image comprises a local type difference.

19. The device according to claim 18, further comprising a separating unit for separating each of the first image and the second image into image blocks each comprising a plurality of pixels.

20. The device according to claim 18, further comprising a relevant image range detecting unit for identifying a relevant image range.

21. A system for automatic detection on clinical relevance of images of an anatomical situation provided by an imaging device, the system comprising:

an imaging device having a permanent video output;

a computer assisted surgical system having an image interface for receiving clinically relevant images; and

a device for automatic detection of clinical relevance of images of an anatomical situation provided by an imaging device, the device comprising;

an image input interface;

a first storage unit for a first image of the anatomical situation taken from the image input interface;

a second storage unit for a second image of the anatomical situation taken from the image input interface;

a comparator unit for comparing and determining a difference between the first image and the second image;

a difference type evaluation unit for evaluating the difference type of the first image and the second image, wherein the difference type evaluation unit is adapted for determining at least one of a local type difference and a global type difference; and

an image selection unit for selecting the second image as having a clinical relevance if it is determined that the difference between the first image and the second image comprises a local type difference,

wherein the image input interface is operatively connected to the permanent video output of the imaging device, and

wherein the image interface for receiving clinically relevant images is operatively connected to the image selection unit.

22. The system of claim 21, wherein the local type difference is a local difference of the first image and the second image.

23. The system of claim 22, wherein the global type difference is a global difference between the first image and the second image.