Method for estimating blood component quantities in surgical textiles

• US 10,424,060 B2
• Filed: 12/23/2016
• Issued: 09/24/2019
• Est. Priority Date: 07/09/2012
• Status: Active Grant

• Current Assignee: Gauss Surgical, Inc. (Stryker Corporation)
• Original Assignee: Gauss Surgical, Inc. (Stryker Corporation)
• Inventors: Satish, Siddarth, Miller, Kevin J., Hosford, Andrew T.
• Primary Examiner(s): Shah, Utpal D
• Application Number:
  US15/390,017
• Publication Number:
  US 20170186160A1
• Time in Patent Office: 1,005 Days
• CPC Class Codes: A61B 2505/05 Surgical care
• CPC Class Codes: A61B 2576/02 specially adapted for a particular organ or body part
• CPC Class Codes: A61B 5/0035 adapted for acquisition of images from more than one imaging mode, e.g. combining MRI and optical tomography
• CPC Class Codes: A61B 5/0082 adapted for particular medical purposes
• CPC Class Codes: A61B 5/02042 Determining blood loss or bleeding, e.g. during a surgical procedure
• CPC Class Codes: A61B 5/1032 Determining colour for diagnostic purposes measuring colour in general G01J3/46
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: G06F 18/24 Classification techniques
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/10028 Range image; Depth image; 3D point clouds
• CPC Class Codes: G06T 2207/10048 Infrared image
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 2207/30104 Vascular flow; Blood flow; Perfusion
• CPC Class Codes: G06T 2207/30242 Counting objects in image
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/62 of area, perimeter, diameter or volume
• CPC Class Codes: G06V 10/56 relating to colour
• CPC Class Codes: G06V 10/764 using classification, e.g. of video objects
• CPC Class Codes: G06V 2201/03 Recognition of patterns in medical or anatomical images
• CPC Class Codes: G16H 30/40 : for processing medical images, e.g. editing

Abstract

Systems and methods for detecting, counting and analyzing the blood content of a surgical textile are provided, utilizing an infrared or depth camera in conjunction with a color image.

Claims

1. A system for measuring blood content, comprising:

a color imaging system configured to acquire a color image of a field of view comprising a surgical textile;

an infrared imaging system configured to acquire an infrared image of the field of view;

a processor configured to;

determine depth information for the surgical textile from the infrared image;

identify surgical textile pixels in the color image; and

extract blood information from the surgical textile pixels.

2. The system of claim 1, wherein the processor is further configured to transform the infrared image to a coordinate system corresponding to the color image.

3. The system of claim 1, wherein the processor is further configured to generate a depth image from the infrared image.

4. The system of claim 3, wherein the processor is further configured to identify a planar set of pixels in the depth image.

5. The system of claim 4, wherein the processor is further configured to detect a surgical textile image perimeter in the depth image.

6. The system of claim 5, wherein the detection of the surgical textile image perimeter is performed by looking for a sharp vertical depth drop-off in the depth image.

7. The system of claim 3, wherein the processor is further configured to downsample the depth image or the infrared image.

8. The system of claim 7, wherein the processor is further configured to generate a mask image from the downsampled depth image.

9. The system of claim 8, wherein the processor is further configured to upsample the mask image.

10. The system of claim 1, wherein the processor is further configured to perform fill-in of a missing infrared pixel region in the infrared image.

11. The system of claim 5, wherein the processor is further configured to generate a mask image using the detected perimeter.

12. The system of claim 11, wherein the processor is further configured to transform the mask image to a coordinate system of the color image.

13. The system of claim 11, wherein the detected perimeter is a top edge and a bottom edge of a surgical textile image.

14. The system of claim 11, wherein the detected perimeter comprises opposing edges of a surgical textile image.

15. The system of claim 11, wherein the detected perimeter comprises corners of a surgical textile image.

16. The system of claim 1, wherein the processor is further configured to index a frame counter upon generating shape information that is characteristic of the surgical textile.

17. A computer-implemented method of analyzing an object containing a blood component, comprising:

acquiring a depth image and a color image of a field of view;

using the depth image to determine the presence of a surgical textile in the field of view; and

using the color image to estimate a characteristic of a blood component contained in the surgical textile.

18. The method of claim 17, further comprising:

generating an image mask using the depth image; and

applying the image mask to the color image to eliminate background pixels.

19. The method of claim 18, further comprising applying at least one of erosion and dilation image processing to the depth image.

20. A computer-implemented method of performing fluid monitoring, comprising:

acquiring a depth image of a surgical textile in a field of view;

acquiring a color image of the surgical textile in the field of view;

generating an image mask using the depth image; and

using the image mask with the color image to identify a region of the color image corresponding to the surgical textile.

21. The method of claim 20, further comprising transforming the infrared image to the geometry perspective of the color image.

22. The method of claim 20, further comprising downsampling the infrared image prior to generating the image mask.

23. The method of claim 22, further comprising upsampling the image mask before using the image mask to identify the region of the color image.