Multispectral imaging and characterization of biological tissue

• US 6,307,957 B1
• Filed: 06/27/2000
• Issued: 10/23/2001
• Est. Priority Date: 02/28/1997
• Status: Expired due to Fees

• Current Assignee: STRATA Skin Sciences, Inc.
• Original Assignee: Electro-Optical Sciences, Inc.
• Inventors: Bogdan, Alexandru, Gutkowicz-Krusin, Dina, Jacobs, Adam, Elbaum, Marek, Greenebaum, Michael
• Primary Examiner(s): Au, Amelia M.
• Assistant Examiner(s): Dastouri, Mehrdad
• Application Number:
  US09/604,645
• Time in Patent Office: 483 Days
• Field of Search: 382/128, 382/133, 382/173, 382/190, 382/191, 382/199, 382/203, 362/574, 348/45, 375/240.19
• US Class Current: 382/128
• CPC Class Codes: A61B 1/00163 Optical arrangements A61B1/002, A61B1/06 take precedence
• 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 5/0084 for introduction into the body, e.g. by catheters A61B5/1459 takes precedence
• CPC Class Codes: A61B 5/442 Evaluating skin mechanical properties, e.g. elasticity, hardness, texture, wrinkle assessment
• CPC Class Codes: A61B 5/445 Evaluating skin irritation or skin trauma, e.g. rash, eczema, wound, bed sore
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06V 20/695 Preprocessing, e.g. image segmentation

Abstract

A light image is conveyed from a biological tissue through a flexible optical system to an image receiver, where it is converted to a form which may be entered into a computer. The computer segments the image by generating a segmentation mask defining the boundary of a region of interest in at least one spectral band, estimates at least one rotationally and translationally invariant statistical measure of coefficient distributions of the multiscale wavelet maxima representations of the digital images in at least one spectral band, characterizes the condition of the tissue based on the estimated values, and outputs the characterization of the condition of the tissue.

Claims

1. A method of characterizing the condition of a region of interest of biological tissue, wherein the absorption and scattering of light in different spectral bands by the region of interest is a function of the condition of the tissue, the method comprising:

illuminating a portion of the tissue including the region of interest by light in at least one spectral band;

conveying an image of the region of interest through an optical system to an image receiver;

imaging a portion of the tissue including the region of interest at the at least one spectral band with the light re-emitted by the portion of the tissue to generate at least one digital image comprising signals whose values are a function of the condition of the region of interest of the tissue; and

providing the digital images to a processor, wherein the processor;

segments the digital images by generating a segmentation mask defining the boundary of the region of interest from a digital image in any one of the at least one spectral bands;

estimates at least one rotationally and translationally invariant statistical measure of coefficient distributions of the multiscale wavelet maxima representations of the digital image;

characterizes the condition of the tissue based on the estimated values; and

outputs the characterization of the condition of the tissue.

2. The method of claim 1, wherein the at least one statistical measure is calculated separately within either of a border region and an interior region of the digital image, wherein:

the border region encompasses the envelope of circles of fixed radius centered on the boundary of the segmentation mask; and

the inside region comprises all points of the image that are within the segmentation mask boundary but not included in the border region.

3. The method of claim 2, wherein the computing step comprises estimating at an individual level at least one value which is a statistical measure of texture of the portion of the region of interest within the border region and interior region, chosen from the group consisting of:

the number of wavelet maxima per unit area;

the ratio of the mean coefficient magnitude to the absolute deviation of the coefficient magnitudes from the mean value;

the ratio of the mean coefficient magnitude to the standard deviation of the coefficient magnitude; and

the skewness of the coefficient magnitude, normalized to the cube of the standard deviation.

4. The method of claim 1, further comprising estimating either of the degree of change of a statistic of the wavelet coefficient distribution with increment of wavelet level, and the degree of deviation of such change from linearity.

5. The method of claim 2, further comprising estimating the average rate of change, with respect to level, of the number of wavelet maxima per unit area.

6. The method of claim 1, further comprising comparing the estimated texture values to the threshold derived from statistical analysis of a multiscale wavelet transformation of the digital image.

7. The method of claim 1, wherein the estimating and characterizing steps are conducted without the intervention of an operator.

8. The method of claim 1, wherein the segmenting step is conducted without the intervention of an operator.

9. The method of claim 1, where the optical system is an endoscope.

10. The method of claim 1, where the optical system is a fiber optic bundle.

11. The method of claim 1, where the optical system is an articulated arm.

12. A system for characterizing the condition of a region of interest of tissue, comprising:

a source of light for illuminating the region of interest in at least one spectral band;

an optical system for conveying the image of the region of interest to an image receiver;

an image receiver for acquiring digital images of the region of interest based on the light re-emitted from the illuminated region of interest at each of the spectral bands, the digital image comprising digital signals whose values are a function of the condition of the region of interest;

memory for storing the digital images provided by the image receiver;

a digital processor programmed to perform the steps of;

segmenting the digital images stored in memory by generating a segmentation mask from a digital image in any one of the at least one spectral band;

estimating at least one rotationally and translationally invariant statistical measure of coefficient distributions for the multiscale wavelet maxima representations of the digital images in each spectral band, which are functions of the texture of the region of interest determined by the segmentation mask;

characterizing the condition of the tissue based on the estimated values; and

outputting the characterization of the region of interest.

13. The system of claim 12, where the flexible optical system is an endoscope.

14. The system of claim 12, where the flexible optical system is a fiber optic bundle.

15. The system of claim 12, where the flexible optical system is an articulated arm.