Method to provide automated quality feedback to imaging devices to achieve standardized imaging data

• US 8,401,258 B2
• Filed: 03/14/2008
• Issued: 03/19/2013
• Est. Priority Date: 03/16/2007
• Status: Expired due to Fees

• Current Assignee: STI Medical Systems LLC
• Original Assignee: STI Medical Systems LLC
• Inventors: Hargrove, John, Gu, Jia, Li, Wenjing, Wolters, Rolf Holger
• Primary Examiner(s): Kim, Robert
• Assistant Examiner(s): OSENBAUGH-STEWART, ELIZA W
• Application Number:
  US12/075,890
• Publication Number:
  US 20080226147A1
• Time in Patent Office: 1,831 Days
• Field of Search: 382/128, 382/274, 382/291
• US Class Current: 382/128
• CPC Class Codes: A61B 5/0084 for introduction into the body, e.g. by catheters A61B5/1459 takes precedence
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/10152 Varying illumination
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 2207/30168 Image quality inspection
• CPC Class Codes: G06T 5/40 using histogram techniques
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 5/90 Dynamic range modification of images or parts thereof
• CPC Class Codes: G06T 7/0002 Inspection of images, e.g. flaw detection
• CPC Class Codes: G06V 10/56 relating to colour

Abstract

Automated image quality assessment algorithms, which perform the functions of locating a region of interest, maximizing the image contrast, and ensuring the region of interest is properly centered in the image. Wherein the region of interest is located by spectral matching filter using a target spectrum obtained from samples of the image itself.

Claims

1. A method to provide automated quality feedback to imaging devices to achieve archive-quality standardized image data for use in electronic medical records and in computer-aided diagnostic (CAD) systems, comprising:

collecting two versions of a raw image from live video during examination with a digital imager, wherein a first version of said raw image is created by illuminating a field of view with a light source having a first polarization orientation and viewing said field of view with a detector through a polarized filter having a second polarization orientation, wherein said first polarization orientation is substantially perpendicular to said second polarization orientation, to produce a cross-polarized image of said field of view, and wherein a second version of said raw image is produced when said second polarization orientation is substantially parallel to said first polarization orientation, to produce a parallel-polarized image of said field of view;

wherein both of said images of said field of view are substantially co-registered, whereby they both have substantially the same borders, each border having a border length and a border width, defining an area within said borders, and a center;

locating a region of interest on said cross-polarized image using an image classification algorithm, wherein said image classification algorithm comprises;

discarding bad image pixels and determining a background mean spectrum,

defining non-overlapping, spatially dispersed samples of substantially uniform size and spacing within said cross-polarized image, and calculating a luminance mean spectrum for each of said samples,

discarding approximately 0-20% of the brightest of said samples and approximately 10-50% of the darkest of said samples, whereby remaining samples are left,

averaging the luminance mean spectra of said remaining samples to determine said a target luminance spectrum, and

determining said region of interest'"'"'s size by ascertaining the portion of said cross-polarized image that substantially matches said target luminance spectrum;

performing contrast maximization by signal assessment and exposure time adjustment to said cross-polarized image and said parallel-polarized image;

applying composition analysis to said cross-polarized image to ensure said region of interest is centered within said cross-polarized image;

determining an assessment status of said contrast maximization and said composition analysis, wherein said assessment status is reported as either a Boolean variable of good or bad;

if said status is bad, repeating said collecting of two versions of a raw image, said locating a region of interest, said performing contrast maximization and said composition analysis; and

if said status is good, collecting a high-resolution cross-polarized still image and a high-resolution parallel-polarized still image.

3. A method according to claim 1 or 2, wherein said image classification algorithm determines said region of interest'"'"'s size using a spectral match filter to estimate a spectral angle between said spectra of the remaining samples and said target spectrum, and wherein said cross-polarized image substantially matches said target spectrum when said spectral angle is less than approximately 65-85 degrees.

4. A method according to claim 1 or 2, wherein said image classification algorithm is performed using spatially dispersed samples of spectra that comprise a plurality of boxes dispersed near said center of said cross-polarized image, each of said boxes having a box length and a box width, and wherein said box lengths are approximately 10-30% of said border length of said cross-polarized image, and wherein said boxes cover approximately 20-60% of said area within said borders of said cross-polarized image.

5. A method according to claim 1 or 2, wherein said image classification algorithm is performed by discarding approximately 10-15% of the brightest and approximately 20-40% of the darkest samples of spectra.

6. A method according to claim 1 or 2, said image classification algorithm is performed by discarding 12% of the brightest and 30% of the darkest sample spectra.

7. A method according to claim 1, wherein said contrast maximization step is performed by adjusting exposure time for said region of interest to generate brightest pixels in said cross-polarized image and said in said parallel-polarized image whose brightness is determined by a digital number, and wherein said brightest pixels have a digital number that falls within a desired range to produce a satisfactory contrast, and wherein the minimum value of said desired range is approximately 80% of the maximum digital number value for said cross-polarized image and is 80% of the maximum digital number value for said parallel-polarized image, and wherein the maximum value of said desired range preferably corresponds to approximately 90% of the maximum digital number value for said cross-polarized image and is approximately 90% of the maximum digital number value for said parallel-polarized image.

9. A method according to claim 1 or 2, wherein said composition analysis step is performed by assessing within said cross-polarized image the proximity of the borders of said region of interest to said borders of said cross-polarized image, determining the proximity of the center of the said region of interest to said center of said cross-polarized image, and calculating the size of said region of interest, and reporting a composition diagnostic message.

10. A method according to claim 9, wherein said composition diagnostic message is reported as satisfactory when said region of interest is centered within said cross-polarized image, is contained within said cross-polarized image borders, and said size of said region of interest is at least approximately 25% of the total area of said cross-polarized image.

11. A method according to claim 1 or 2, wherein said Boolean variable of good applies only when said contrast maximization and said composition analysis are satisfactory.

12. A method according to claim 1 or 2, wherein said Boolean variable of bad applies when either said contrast maximization or said composition analysis are unsatisfactory or when both contrast maximization and said composition analysis are unsatisfactory.

2. A method to provide automated quality feedback to imaging devices to achieve archive-quality standardized image data for use in electronic medical records and in computer-aided diagnostic (CAD) systems, comprising:

collecting two versions of a raw image from live video during examination with a digital imager, wherein a first version of said raw image is created by illuminating a field of view with a light source having a first polarization orientation and viewing said field of view with a detector through a polarized filter having a second polarization orientation, wherein said first polarization orientation is substantially perpendicular to said second polarization orientation, to produce a cross-polarized image of said field of view, and wherein a second version of said raw image is obtained by placing a polarized filter at a location selected from the group consisting of said light source and said detector, to produce a singly-polarized image of said field of view;

wherein both of said images of said field of view are substantially co-registered, whereby they both have substantially the same borders, each border having a border length and a border width, defining an area within said borders, and a center;

locating a region of interest on said cross-polarized image using an image classification algorithm, wherein said image classification algorithm comprises;

discarding bad image pixels and determining a background mean spectrum,

defining non-overlapping, spatially dispersed samples of substantially uniform size and spacing within said cross-polarized image, and calculating a luminance mean spectrum for each of said samples,

discarding approximately 0-20% of the brightest of said samples and approximately 10-50% of the darkest of said samples, whereby remaining samples are left,

averaging the luminance mean spectra of the said remaining samples to determine a target luminance spectrum, and

determining said region of interest'"'"'s size by ascertaining the portion of said cross-polarized image that substantially matches said target luminance spectrum;

performing contrast maximization by signal assessment and exposure time adjustment to said cross-polarized image and said singly-polarized image;

applying composition analysis to said cross-polarized image to ensure said region of interest is centered within said cross-polarized image;

determining an assessment status of said contrast maximization and said composition analysis, wherein said assessment status is reported as either a Boolean variable of good or bad;

if said status is bad, repeating said collecting of two versions of a raw image, said locating a region of interest, said performing contrast maximization and said composition analysis; and

if said status is good, collecting a high-resolution cross-polarized still image and a high-resolution singly-polarized still image.

8. A method according to claim 2, wherein said contrast maximization step is performed by adjusting exposure time for said region of interest to generate brightest pixels in said cross-polarized image and in said singly-polarized image whose brightness is determined by a digital number, and wherein said brightest pixels have a digital number that falls within a desired range to produce a satisfactory contrast, and wherein the minimum value of said desired range is approximately 80% of the maximum digital number value for said cross-polarized image and is 80% of the maximum digital number value for said singly-polarized image, and wherein the maximum value of said desired range preferably corresponds to approximately 90% of the maximum digital number value for said cross-polarized image and is approximately 90% of the maximum digital number value for said singly-polarized image.

13. A method to provide automated quality feedback to imaging devices to achieve archive-quality standardized image data for use in electronic medical records and in computer-aided diagnostic (CAD) systems, comprising:

collecting two versions of a raw image from live video during examination with a digital imager, wherein a first version of said raw image is created by illuminating a field of view with a light source having a first polarization orientation and viewing said field of view with a detector through a polarized filter having a second polarization orientation, wherein said first polarization orientation is substantially perpendicular to said second polarization orientation, to produce a cross-polarized image of said field of view, and wherein a second version of said raw image is produced when said second polarization orientation is substantially parallel to said first polarization orientation, to produce a parallel-polarized image of said field of view;

wherein both of said images of said field of view are substantially co-registered, whereby they both have substantially the same borders, each border having a border length and a border width, defining an area within said borders, and a center;

locating a region of interest on said cross-polarized image using an image classification algorithm, wherein said image classification algorithm comprises;

discarding bad image pixels and determining a background mean spectrum,

defining non-overlapping, spatially dispersed samples of substantially uniform size and spacing within said cross-polarized image, and calculating a luminance mean spectrum for each of said samples,

discarding approximately 0-20% of the brightest of said samples and approximately 10-50% of the darkest of said samples, whereby remaining samples are left,

averaging the luminance mean spectra of the said remaining samples to determine a target luminance spectrum, and

determining said region of interest'"'"'s size by ascertaining the portion of said cross-polarized image that substantially matches said target luminance spectrum;

performing contrast maximization by signal assessment and exposure time adjustment to said cross-polarized image and said parallel-polarized image by adjusting exposure time for said region of interest to generate brightest pixels in said cross-polarized image and in said parallel-polarized image whose brightness is determined by a digital number, and wherein said brightest pixels have a digital number that falls within a desired range to produce a satisfactory contrast, and wherein the minimum value of said desired range is approximately 80% of the maximum digital number value for said cross-polarized image and is 80% of the maximum digital number value for said parallel-polarized image, and wherein the maximum value of said desired range preferably corresponds to approximately 90% of the maximum digital number value for said cross-polarized image and is approximately 90% of the maximum digital number value for said parallel-polarized image;

applying composition analysis to said cross-polarized image by assessing within said cross-polarized image the proximity of the borders of said region of interest to said borders of said cross-polarized image, determining the proximity of the center of the said region of interest to said center of said cross-polarized image, and calculating the size of said region of interest, and reporting a composition diagnostic message, wherein said composition diagnostic message is reported as satisfactory when said region of interest is centered within said cross-polarized image, is contained within said cross-polarized image borders, and said size of said region of interest is at least approximately 25% of the total area of said cross-polarized image;

determining an assessment status of said contrast maximization and said composition analysis, wherein said assessment status is reported as either a Boolean variable of good or bad, and wherein said Boolean variable of good applies only when said contrast maximization and said composition analysis are satisfactory, and wherein said Boolean variable of bad applies when either said contrast maximization or said composition analysis are unsatisfactory or when both contrast maximization and said composition analysis are unsatisfactory;

if said status is bad, repeating said collecting of two versions of a raw image, said locating a region of interest, said performing contrast maximization and said composition analysis; and

if said status is good, collecting a high-resolution cross-polarized still image and a high-resolution parallel-polarized still image.

14. A method to provide automated quality feedback to imaging devices to achieve archive-quality standardized image data for use in electronic medical records and in computer-aided diagnostic (CAD) systems, comprising:

collecting two versions of a raw image from live video during examination with a digital imager, wherein a first version of said raw image is created by illuminating a field of view with a light source having a first polarization orientation and viewing said field of view with a detector through a polarized filter having a second polarization orientation, wherein said first polarization orientation is substantially perpendicular to said second polarization orientation, to produce a cross-polarized image of said field of view, and wherein a second version of said raw image is obtained by placing a polarized filter at at-a location selected from the group consisting of said light source and said detector, to produce a singly-polarized image of said field of view;

wherein both of said images of said field of view are substantially co-registered, whereby they both have substantially the same borders, each border having a border length and a border width, defining an area within said borders, and a center;

locating a region of interest on said cross-polarized image using an image classification algorithm, wherein said image classification algorithm comprises;

discarding bad image pixels and determining a background mean spectrum,

defining non-overlapping, spatially dispersed samples of substantially uniform size and spacing within said cross-polarized image, and calculating a luminance mean spectrum for each of said samples,

discarding approximately 0-20% of the brightest of said samples and approximately 10-50% of the darkest of said samples, whereby remaining samples are left,

averaging the luminance mean spectra of said remaining samples to determine a target luminance spectrum, and

determining said region of interest'"'"'s size by ascertaining the portion of said cross-polarized image that substantially matches said target luminance spectrum;

performing contrast maximization by signal assessment and exposure time adjustment to said cross-polarized image and said singly-polarized image by adjusting exposure time for said region of interest to generate brightest pixels in said cross-polarized image and in said singly-polarized image whose brightness is determined by a digital number, and wherein said brightest pixels have a digital number that falls within a desired range to produce a satisfactory contrast, and wherein the minimum value of said desired range is approximately 80% of the maximum digital number value for said cross-polarized image and is 80% of the maximum digital number value for said singly-polarized image, and wherein the maximum value of said desired range preferably corresponds to approximately 90% of the maximum digital number value for said cross-polarized image and is approximately 90% of the maximum digital number value for said singly-polarized image;

applying composition analysis to said cross-polarized image by assessing within said cross-polarized image the proximity of the borders of said region of interest to said borders of said cross-polarized image, determining the proximity of the center of the said region of interest to said center of said cross-polarized image, and calculating the size of said region of interest, and reporting a composition diagnostic message, wherein said composition diagnostic message is reported as satisfactory when said region of interest is centered within said cross-polarized image, is contained within said cross-polarized image borders, and said size of said region of interest is at least approximately 25% of the total area of said cross-polarized image;

determining an assessment status of said contrast maximization and said composition analysis, wherein said assessment status is reported as either a Boolean variable of good or bad, and wherein said Boolean variable of good applies only when said contrast maximization and said composition analysis are satisfactory, and wherein said Boolean variable of bad applies when either said contrast maximization or said composition analysis are unsatisfactory or when both contrast maximization and said composition analysis are unsatisfactory;

if said status is bad, repeating said collecting of two versions of a raw image, said locating a region of interest, said performing contrast maximization and said composition analysis; and

if said status is good, collecting a high-resolution cross-polarized still image and a high-resolution singly-polarized still image.