Method of assessing a body part

• US 7,702,140 B2
• Filed: 02/23/2009
• Issued: 04/20/2010
• Est. Priority Date: 09/09/2004
• Status: Active Grant

• Current Assignee: Carnegie Mellon University
• Original Assignee: Carnegie Mellon University
• Inventors: Hirsch, Raphael, Huber, Daniel, Osborn, James, Denes, Louis J., Kwoh, Chian Kent
• Primary Examiner(s): AZARIAN, SEYED H
• Application Number:
  US12/391,183
• Publication Number:
  US 20090214092A1
• Time in Patent Office: 421 Days
• Field of Search: 382/100, 382/103, 382/108, 382/128, 382/129, 382/130, 382/131, 382/133, 382/134, 382/168, 382/181, 382/193, 382/199, 382/203, 382/210, 382/224, 382/232, 382/274, 382/276, 382/285, 382/305, 382/154, 280/33.991, 427/140, 600/420, 600/416, 600/427, 600/474, 378/41
• US Class Current: 382/128
• 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 5/0062 Arrangements for scanning
• CPC Class Codes: A61B 5/0064 Body surface scanning
• CPC Class Codes: A61B 5/015 By temperature mapping of body part
• CPC Class Codes: A61B 5/103 Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes A61B5/08 takes precedence; measuring aids for tailors A41H1/00; measuring instruments specially adapted for dentistry A61C19/04
• CPC Class Codes: A61B 5/4528 Joints A61B5/4533, A61B5/4538 take precedence
• CPC Class Codes: G06F 18/21 Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
• CPC Class Codes: G06T 2207/20212 Image combination
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06V 10/70 using pattern recognition or machine learning optical pattern recognition or electronic computations therefor G06V10/88
• CPC Class Codes: G06V 40/11 Hand-related biometrics; Hand pose recognition

Abstract

A method of assessing a body part includes obtaining two or more types of data through a combination of two or more of the following four imaging modalities: (1) obtaining surface topography data of the body part, (2) obtaining thermographic data of the body part, (3) obtaining range of motion data for the body part, and (4) obtaining spectral data of light reflected from the body part. The two or more types of data are integrated to allow them to be interacted with simultaneously, and the body part is assessed based on the integrated data.

Claims

1. A method of assessing a body part, comprising

(A) obtaining two or more types of data through a combination of two or more imaging modalities conducted on said body part, each of said two or more imaging modalities being selected from the group consisting of (1) through (4) as set forth below:

(1) obtaining surface topography data of said body part through a method comprising;

(a) imaging said body part with a three-dimensional scanner from one or more angles to produce one or more scanned images of said body part; and

(b) creating a three-dimensional surface model of said body part from said one or more scanned images;

(2) obtaining thermographic data of said body part through a method comprising imaging said body part with a thermal camera to produce a thermal image;

(3) obtaining range of motion data for said body part through a method comprising;

(a) moving said body part through its entire range of motion; and

(b) calculating extrema of said range of motion; and

(4) obtaining spectral data of light reflected from said body part;

(B) integrating the two or more types of data such that the two or more types of data can be interacted with simultaneously; and

(C) assessing said body part based on the integrated data.

2. The method of claim 1, wherein the two or more types of data comprise data obtained from imaging modality (1), wherein imaging modality (1) further comprises immobilizing said body part prior to imaging said body part with the three-dimensional scanner.

3. The method of claim 2, wherein the immobilizing step comprises placing said body part in a pre-molded cast.

4. The method of claim 1, wherein the two or more types of data comprise data obtained from imaging modality (1), wherein the three-dimensional scanner comprises a laser line triangulation scanner.

5. The method of claim 1, wherein the two or more types of data comprise data obtained from imaging modality (1), wherein imaging modality (1) further comprises:

(c) comparing the three-dimensional surface model to a reference model to assess a change in volume between the three-dimensional surface model and the reference model.

6. The method of claim 5, wherein the reference model comprises a previously imaged model of the same body part.

7. The method of claim 5, wherein the reference model comprises a model simulated from a normative sample of similar body parts.

8. The method of claim 5, wherein said body part comprises is assessed for the presence of swelling based on the change in volume.

9. The method of claim 5, wherein said body part is assessed for the severity of swelling based on the change in volume.

10. The method of claim 9, wherein the severity of swelling is represented by a numerical indicator.

11. The method of claim 1, wherein the two or more types of data comprise data obtained from imaging modality (2), wherein the thermographic data provides a heat distribution index.

12. The method of claim 1, wherein the two or more types of data comprise data obtained from imaging modality (3), wherein said imaging modality (3) is conducted at multiple time points so as to detect a change in range of motion.

13. The method of claim 12, wherein the detected change in range of motion correlates with a numerical indicator that can be integrated with the three-dimensional surface model and the two-dimensional thermal image.

14. The method of claim 1, wherein the two or more types of data comprise data obtained from imaging modality (4), wherein the spectral data of light provides a color map of areas affected by erythema.

15. The method of claim 1, wherein the two or more types of data comprise data obtained from imaging modality (4), wherein the spectral data of light correlates with a numerical indicator for erythema of said body part.

16. The method of claim 1, wherein the two or more types of data comprise data obtained from imaging modality (4), wherein the spectral data include near-infrared data imaged with a near-infrared imager to produce a near-infrared image.

17. The method of claim 16, wherein the degree of erythema is assessed from the near-infrared image.

18. The method of claim 16, wherein the two or more types of data are obtained from imaging modalities (1), (2) and (4), wherein integrating the data comprises integrating the near-infrared image with the three-dimensional surface model and the thermal image to provide an overall assessment of said body part.

19. The method of claim 16, wherein the near-infrared imager images a range of wavelengths between 700 nm and 1100 nm.

20. The method of claim 1, wherein the two or more types of data are obtained from imaging modalities (1) and (2), and wherein integrating the data comprises texture-mapping the thermal image onto the three-dimensional surface model.

21. The method of claim 1, wherein the two or more types of data are obtained from imaging modalities (1) and (2), and wherein integrating the data comprises projecting the three-dimensional surface model onto the thermal image.

22. The method of claim 1, wherein the two or more types of data are obtained from imaging modalities (1) and (2), and wherein integrating the three-dimensional surface model and the thermal image results in a composite index comprising volume and temperature components.

23. The method of claim 22, wherein the composite index is used to quantify symptoms of a disease.

24. The method of claim 23, wherein the symptoms comprise swelling or heat distribution.

25. The method of claim 23, wherein the disease comprises arthritis.

26. The method of claim 1, wherein the two or more types of data are obtained from imaging modalities (1) and (2), and wherein integrating the three-dimensional surface model and the thermal image shows a correlation between symptoms of diseases.

27. The method of claim 1, wherein the two or more types of data are obtained from imaging modalities (1) and (3), and wherein integrating the three-dimensional surface model and the range of motion data shows a correlation between symptoms of diseases.

28. The method of claim 1, wherein the two or more types of data are obtained from imaging modalities (1) and (4), and wherein integrating the three-dimensional surface model and the range of motion data shows a correlation between symptoms of diseases.

29. The method of claim 1, wherein the two or more types of data are obtained from imaging modalities (2) and (4), and wherein integrating the thermographic data and spectral data of light shows a correlation between symptoms of diseases.

30. The method of claim 1, wherein the two or more types of data comprise data obtained from imaging modality (1), wherein said body part is assessed for cancer based on the surface topography data.

31. The method of claim 1, wherein the two or more types of data comprise data obtained from imaging modality (1), wherein said body part is assessed for arthritis.

32. The method of claim 1, wherein the two or more types of data comprise data obtained from imaging modality (1), wherein said body part is assessed for changes in size and shape of skin lesions based on the surface topography data.

33. The method of claim 1, wherein the two or more types of data comprise data obtained from imaging modality (2), wherein said body part is assessed for variations in temperature based on the thermographic data.