System and method for assessing wound

1. A method for assessing chronic wounds and ulcers, comprising:

capturing an image of a body part including a wound area; the image being a color image;

segmenting the image;

determining a boundary of the wound area;

performing color segmentation within the boundary, wherein the wound area is divided into a plurality of segments, each segment being associated with a color indicating a healing condition of the segment;

and

evaluating the wound area; wherein a wound evaluation component is configured to determine a quantitative healing score as a method for quantifying a healing status of the wound area; wherein the quantitative healing score is a wound evaluation value; wherein the quantitative healing score is based on a weighted wound area; the weighted wound area being a weighted sum of red tissue wound area, yellow tissue wound area, and black tissue wound area; wherein, weights being predetermined; the quantitative healing score also being based on a ratio of the weighted wound area to a weighted wound area for an initial wound image for a same subject; the quantitative healing score comprising a difference between a first predetermined constant and a product of a second predetermined constant and the ratio of the weighted wound area to the weighted wound area for the initial wound image for the same subject;

wherein the method is used for assessing chronic wounds and ulcers including chronic foot wounds and ulcers from type 2 diabetes.

2. The method of claim 1 , wherein segmenting the image comprises performing mean shift segmentation.

3. The method of claim 2 , wherein the segmenting comprises merging an over segmented image into a smaller number of regions.

4. The method of claim 1 , wherein determining the boundary of the wound area comprises using a conditional random field method.

5. The method of claim 1 , wherein performing the color segmentation comprises:

performing a K-mean color clustering algorithm.

6. The method of claim 1 , wherein the body part also includes a calibration patch; the calibration patch located proximate to the wound area and substantially in a same plane as the wound area; the calibration patch comprising a number of concentric, circular areas; and

wherein the method further comprises:

locating the calibration patch and the number of concentric, circular areas;

determining, from a location of the calibration patch and the number of concentric, circular areas, whether the image was acquired at an angle relative to normal incidence; and

correcting, when the image was acquired at the angle relative to normal incidence, the wound area.

7. The method of claim 6 , wherein correcting the wound area comprises multiplying an observed wound area by a square of a ratio of a reference range, the reference range being a range at which a conversion factor between wound area in pixels and wound area in mm 2 has been determined, to a range at which the observed wound area was observed, and dividing by the cosine of the angle relative to normal incidence.

8. A system for assessing wound, comprising:

an image acquisition device configured for capturing an image of a body part including a wound area; the image being a color image; and

one or more processors configured to:

segment the image into a number of regions;

extract a boundary of the wound area;

perform color segmentation within the boundary of the wound area, wherein the wound area is divided into a plurality of segments, each segment being associated with a color indicating a healing condition of the segment; and

evaluate the wound area; wherein a wound evaluation component is configured to determine a quantitative healing score as a method for quantifying a healing status of the wound area; wherein the quantitative healing score is a wound evaluation value;

wherein the quantitative healing score is based on a weighted wound area; the weighted wound area being a weighted sum of red tissue wound area, yellow tissue wound area, and black tissue wound area; wherein, weights being predetermined; the quantitative healing score also being based on a ratio of the weighted wound area to a weighted wound area for an initial wound image for a same subject; the quantitative healing score comprising a difference between a first predetermined constant and a product of a second predetermined constant and the ratio of the weighted wound area to the weighted wound area for the initial wound image for the same subject;

wherein the system is used for assessing chronic wounds and ulcers including chronic foot wounds and ulcers from type 2 diabetes.

9. The system of claim 8 , wherein segmenting the image comprises performing mean shift segmentation.

10. The system of claim 9 , wherein the segmenting comprises merging an over segmented image into a smaller number of regions.

11. The system of claim 8 , wherein determining the boundary of the wound area comprises using a conditional random field method.

12. The system of claim 8 , wherein performing color segmentation within the boundary of the wound area comprises performing a K-mean color clustering algorithm; and uses a red-yellow-black evaluation model for evaluation of the color segmentation.

13. The system of claim 8 , wherein the body part also includes a calibration patch; the calibration patch located proximate to the wound area and substantially in a same plane as the wound area; the calibration patch comprising a number of concentric, circular areas; and

wherein the one or more processors are further configured to:

determine a location of the calibration patch and the number of concentric, circular areas;

determine, from the location of the calibration patch and the number of concentric, circular areas, whether the image was acquired at an angle relative to normal incidence; and

 correct, when the image was acquired at the angle relative to normal incidence, the wound area.

14. The system of claim 13 wherein correcting the wound area comprises multiplying an observed wound area by a square of a ratio of a reference range, the reference range being a range at which a conversion factor between wound area in pixels and wound area in mm 2 has been determined, to a range at which the observed wound area was observed, and dividing by the cosine of the angle relative to normal incidence.

15. The system of claim 8 , wherein the system comprises a computing component and the image acquisition device is comprised in a handheld portable electronic device; and wherein the handheld portable electronic device comprises:

one or more other processors; and

non-transitory first computer usable media having computer readable code that, when executed by the one or more other processors, causes the one or more other processors to:

transmit the image to the computing component;

and wherein the computing component comprises:

the one or more processors; and

non-transitory second computer usable media having computer readable code that, when executed by the one or more processors, configures the one or more processors.

16. The system of claim 8 further comprising:

an imaging component comprising:

a first front surface mirror; and

a second front surface mirror; the second front surface mirror being disposed at a right angle to the first front surface mirror;

wherein the imaging component is configured such that the body part is positioned above the first and second front surface mirrors and away from an axis bisecting the right angle; and

wherein the image acquisition device is positioned above the first and second front surface mirrors, away from the axis bisecting the right angle and on an opposite side of the axis bisecting the right angle from the body part.