System, method and computer program product for screening a spectral image

• US 20040024296A1
• Filed: 08/08/2003
• Published: 02/05/2004
• Est. Priority Date: 08/27/2001
• Status: Abandoned Application

• Current Assignee: Intelligent Medical Devices, Inc.
• Original Assignee: Intelligent Medical Devices, Inc.
• Inventors: Krotkov, Eric P., Zhong, Zhang, Danen, Robert M., Wang, Yongping
• Application Number:
  US10/362,643
• Publication Number:
  US 20040024296A1
• Time in Patent Office: Days
• US Class Current: 600/322
• CPC Class Codes: A61B 5/0059 using light, e.g. diagnosis by transillumination, diascopy, fluorescence A61B5/0093, A61B5/1455, A61B5/02416 and A61B5/0261 take precedence
• CPC Class Codes: A61B 5/14535 for measuring haematocrit
• CPC Class Codes: A61B 5/1455 using optical sensors, e.g. spectral photometrical oximeters
• CPC Class Codes: A61B 5/411 Detecting or monitoring allergy or intolerance reactions to an allergenic agent or substance
• CPC Class Codes: A61B 5/7253 characterised by using transforms
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/726 using Wavelet transforms

Abstract

A system, method and computer program product is provided for screening and analyzing spectral images of a microcirculatory system to measure blood characteristics, such as hemoglobin concentration. In an embodiment, multi-stage screening is performed on each input image to determine whether the image is suitable for hemoglobin measurement and prediction. During the screening process the following quantities are measured: image intensity, image background intensity variation, image focus condition, image motion blur condition, number of vessels in the image with certain range of diameters, average vessel edge contrast, number of bubble segments in the image and the similarity between two images. The multi-stage screening cycle includes intensity screening, DWT decomposition, focus measurement, motion blur measurement, vessel and bubble detection, and repetition detection. During the screening stages, the image is classified into one of three categories: excellent, mediocre and poor. Only the images with an excellent rating is used for further Hb estimation. But both excellent and mediocre images would launch an autofocusing process provided by focus measurement. In another embodiment, a Fast Fourier transform is used to develop a spectral ratio to detect excellent images. The present invention provides real time hemoglobin prediction on the subject under investigation.

Claims

1. A method for screening images of visualizable components in a fluid flowing in a vascular system, the walls of which are substantially transparent to transmitted and reflected light, using a light transmitting device that is capable of transmitting light through the walls of a region of the vascular system into a sub-surface region thereof, an image capturing device capable of capturing images reflected from the sub-surface region of the vascular system illuminated by the light transmitting device to create a spectral image, and a processing unit in communication with the image capturing device, comprising the steps of:

receiving in the processing unit a reflected spectral image of the subsurface region captured by the image capturing device;

screening said reflected spectral image to determine whether said reflected spectral image passes a screening stage, wherein said reflected spectral image passes said screening stage if at least one of a plurality of properties of said reflected spectral image exceeds a predetermined threshold; and

analyzing said reflected spectral image to measure an optical density of the vascular region to estimate hemoglobin, provided that said reflected spectral image passes said screening stage.

2. An method of claim 1, wherein said screening step further comprises:

uniformly extracting a predetermined number of rows and columns from said reflected spectral image to produce a subsampled image, wherein screening information is derived from said subsampled image for real time screening.

3. An method of claim 2, wherein said screening step further comprises:

evaluating said subsampled image to determine a mean image intensity value and a mean intensity variation value.

4. An method of claim 2, wherein said screening step further comprises:

performing DWT on said subsampled image to derive DWT coefficients for said rows and said columns at three decomposition scales.

5. An method of claim 2, wherein said screening step further comprises:

computing focus measurements from high frequency components of said subsampled image at a designated decomposition scale, wherein said focus measurements are used to compare focus conditions of said reflected spectral image and a controlled image.

6. An method of claim 5, wherein said focus measurements are automatically implemented to analyze an average vessel edge contrast of said reflected spectral image to determine if said reflected spectral image is out of focus.

7. An method of claim 5, wherein said screening step further comprises:

generating a binary vessel mask for said reflected spectral image, wherein said binary vessel mask includes a row mask and column mask.

8. An method of claim 7, wherein said screening step further comprises:

analyzing said focus measurements and said binary vessel mask for repetition detection to determine if said reflected spectral image and said controlled image are from the same site.

9. An method of claim 8, wherein said reflected spectral image passes said screening stage if said focus measurements of said reflected spectral image are higher than focus measurements of said controlled image.

10. An method of claim 1, wherein said screening step further comprises:

computing a motion blur measurement for said reflected spectral image.

11. An method of claim 10, wherein said screening step further comprises:

comparing said motion blur measurement to a motion blur threshold to detect motion blur, wherein said reflected spectral image does not pass said screening stage if motion blur is detected.

12. An method of claim 1, wherein said screening step further comprises:

performing vessel and bubble detection to determine the presence of good-sized vessels and bubbles in said reflected spectral image.

13. An method of claim 12, wherein the number of good-sized vessels and bubbles are compared to predetermined thresholds and said reflected spectral image does not pass said screening stage if said number of good-sized vessels or said number of bubbles exceeds said predetermined thresholds.

14. An method of claim 1, wherein said screening step further comprises:

cropping and subsampling said reflected spectral image according to a predetermined parameter to produce a subsampled image.

15. An method of claim 14, wherein said screening step further comprises:

applying a Fast Fourier transform to compute a power spectrum for said subsampled image.

16. An method of claim 15, wherein said screening step further comprises:

determining slopes of said power spectrum at low and intermediate spatial frequencies.

17. An method of claim 16, wherein said screening step further comprises:

deriving a spectral ratio from said slopes.

18. An method of claim 17, wherein said screening step further comprises:

evaluating said spectral ratio, wherein said reflected spectral image passes said screening stage if said spectral ratio falls within a predetermined range.

19. For use with a light transmitting device for transmitting light through a vascular system, and an image capturing device for capturing images from the vascular system illuminated by the light transmitting device to create a spectral image, a processing unit adapted for communication with the image capturing device for analyzing at least one visualizable component in a fluid flowing in the vascular system, the walls of which are substantially transparent to transmitted and reflected light, comprising:

receiving means for receiving a reflected spectral image of the vascular system captured by said image capturing device;

screening means for screening said reflected spectral image to determine whether said reflected spectral image passes a screening stage, wherein said reflected spectral image passes said screening stage if at least one of a plurality of properties of said reflected spectral image exceeds a predetermined threshold; and

analyzing means for measuring an optical density of the vascular system to estimate hemoglobin.

20. A computer program product comprising a computer useable medium having computer readable program code means embedded in said medium for causing an application program to execute on a computer that analyzes visualizable components in a fluid flowing in a vascular system, the walls of which are substantially transparent to transmitted and reflected light, using a light transmitting device that is capable of transmitting light through the vascular system, and an image capturing device capable of capturing images from the vascular system illuminated by the light transmitting device to create a spectral image, comprising:

a first computer readable program code means for causing the computer to receive a reflected spectral image of the vascular system captured by the image capturing device;

a second computer readable program code means for causing the computer to screen said reflected spectral image to determine whether said reflected spectral image passes a screening stage, wherein said reflected spectral image passes said screening stage if at least one of a plurality of properties of said reflected spectral image exceeds a predetermined threshold; and

a third computer readable program code means for causing the computer to measure an optical density of the vascular system to estimate hemoglobin, provided that said reflected spectral image passes said screening stage to determine whether at least one of a plurality of properties of said reflected spectral image exceeds a predetermined threshold.