Special training laboratory on optical biophysics. Education-research setups for postgraduate students
Ivan V. Fedosov, Alexey N. Bashkatov, Elina A. Genina, Georgy V. Simonenko, Dmitry A. Zimnykov, and Valery V. Tuchin' Saratov State University, Saratov, RU 410026

ABSTRACT

The set of educational-research practical works for postgraduate students of the special training laboratory on optical biophysics is described. Presented materials were also discussed on SPIE 7thi International Conference on Education and Training in Optics and Phoptonics 2001 (ETOP), 26-30 November, 2001.
Keywords: optical biophysics, spectroscopy, scattering media, speckles, Doppler system, color imaging, skin, training laboratory.

1. INTRODUCTION

This paper presents the set of practical works of the training laboratory on optical biophysics'5 for postgraduate
students. This set ofpractical works consists ofthe following setups: I. Laser Doppler velocimeter 2. Speckle-interferometric instrument for monitoring of capillary bio-flow 3. Two-wavelength laser scanning microphotometer 4. Spatial RGB analyzer ofbiological objects 5. Spatial-resolved microspectrophotometer for tissue optical properties and geometry studies: CCD tester
The requirements to a learning person: background in light scattering, tissue optics and spectroscopy.68
2. LASER DOPPLER VELOCIMETER
This practical work will enable students: to understand principles of optical heterodyning and digital signal
processing, to get an overview of principles and schemes of laser instruments such as laser Doppler anemometers
Basic kit: laser Doppler velocimeter; rotating screen with motor; set oftransparent tubes and scattering fluid.
Optical scheme of experimental setup is presented in Fig. 1. A typical Doppler frequency shift power spectrum obtained with
rotating disk can be found in Fig. 2.
Examples of practical tasks available with the basic kit:
Investigation of physical principles of LDA using rotating scattering screen. Investigation of flow velocity distribution in the tube for Newtonian and non-Newtonian (whole blood) liquids. 3. Development of digital signal processing and analysis for flow dynamics monitoring.
Department of Physics, Saratov State University, 155, Moskovskaya str., Saratov, 410026, Russia; tel/office: +7 (8452) 5 1-46-93, fax: +7 (8452) 24-04-46; e-mail: tuchinsgu.ru
Saratov Fall Meeting 2001: Optical Technologies in Biophysics and Medicine III, Valery V. Tuchin, Editor, Proceedings of SPIE Vol. 4707 (2002) 2002 SPIE 0277-786X/02/$15.00
Laser diode module ? = 650 rim

Prismatic wavefront

spUrner
Fig. I: Optical scheme of laser Doppler velocimeter
Fig.2: Doppler frequency shift power spectrum obtained with rotating disk.
SPECKLE-INTERFEROMETRIC INSTRUMENT FOR MONITORING OF CAPILLARY BlOFLOW
This practical work will enable students: to get an overview of dynamic speckles properties; to identify the time
correlation-spectral and space correlation approaches in speckle dynamics analysis; to understand the basic principles of homodyne photodetection and speckle- interferometry.
Experimental setup is presented in Fig. 3. It allows for bio-flow velocity and direction monitoring and investigation of speckle field statistical properties.
Two plots characterizing space-time correlation of dynamic speckle field: the space-time correlation function and calibration curve for translation velocity of speckles are presented in Figs. 4 and 5.

Proc. SPIE Vol. 4707

Plastic capillary tube

Personal computer

Fig.3: Speckle-interferometric instrument for monitoring of capillary bio-flow.

V$=s/zd

Wv -100

Vr, rel. units

Fig. 4: Dynamic speckle field space-time correlation.
Correlation function estimate.
Fig.5: Plot ofspeckle translation velocity
Examples of tasks for students:
Investigation of dynamic speckle field time-dependent intensity fluctuations in a fixed point. Investigation of dynamic speckle field space-time correlation. Monitoring of non-stationary capillary flow.
4. TWO-WAVELENGTH LASER SCANNING MICROPHOTOMETER
This practical work will enable students: to get an overview of tissue optical properties; to understand principles of photometry; to analyze spectral images of tissue samples.
Optical scheme of two-wavelength laser scanning microphotometer is presented in Fig. 6. Single and wo-wavelength images in Fig. 7 illustrate the diagnostic possibilities of the instrument.
Examples of tasks for students: investigation of pigment absorption at different wavelengths and concentrations
imaging oftissue sample at two wavelengths; programming ofautomated sample scanning.

783 nm laser diode

648 nm laser diode

Eyepiece

Microscope objective

Filter

splitter

Microscope

objectiVe

control module

Personal

computer

2-D motorized positioning stage
Fig. 6: Optical scheme of two-wavelength laser scanning microphotometer.

1TT TT T 648nm

783 nm

Difference

Filtered difference
Fig. 7: Images ofthe epilated human hairs at single and two wavelengths (difference and filtered difference). In v/ye stained by Indocyanine green (left images) and natural (right images) hairs.
5. SPATIAL RGB ANALYZER OF BIOLOGICAL OBJECTS
This practical work enables students: to obtain knowledge ofprinciple ofdigital analysis ofcolor image of biological objects; to study technique for measurement of transmittance and reflectance of biological objects using their digital images; to study inverse Monte Carlo method for estimation oftissue optical properties; to estimate optical properties of human hair by inverse Monte Carlo method and spatial digital image analysis.
Digital imaging is a method whereby images are represented by a series ofnurnbers. Each number usually represents a measure of energy reflected from a tiny elemental portion of the structure that is being imaged. In two-dimensional imaging, this tiny picture element is called a pixel, is usually rectangular, and is displayed as a single dot in digital image. Color resolution (pixel depth) refers to the number of bits of information that are used to represent either the number of shades of gray or number of colors that each pixel can represent. Eight bits of information can represent 28=256 shades of gray or 256 different colors. In 24-bit true color images, 8-bits (256 shades) for each of three primary colors (usually red, green, and blue) have been using. To evaluate the clinical morphology ofdifferent skin lesions (pigmentation, psoriasis, erythema, etc.), measurement of hair growth, wound healing, and burn management digital imaging methods have been applying. Digital imaging techniques combined with inverse Monte Carlo method can be also used for estimation of optical properties of human hair shafts.

To obtain optical properties ofthe human hairs the following steps have to be done: (1) to record images ofthe hair in both reflectance and transmittance modes using experimental setup (Fig. 8); (2) to process obtained images with the developed software allowing for getting of selected red, green, and blue components of the image; (3) to determine reflectance and transmittance ofthe hair for each color components; (4) to calculate the optical properties ofa hair shaft (absorption and reduced scattering coefficients) using experimental data for reflectance and transmittance and inverse Monte Carlo method.
Fig. 8: Video-microscopic system for spatial digital color analysis of biological objects: 1 PC.
microscope. 4 light sources for transmittance or reflectance measurements, 5 biological object.

2 CUD-camera. 3 light

The color imaging system is composed of a video-microscope (SVHS Sony CCD-TR617E, PAL, Japan (2) and light microscope (3)) interfaced with a personal computer (1). The specimen (plane plate with attached biological object) (5) is illuminated by white light (halogen lamps (4) provide illumination for recording of transmittance or reflectance
images. In dependence on mode of the illumination the specimen plate presents either transparent glass plate (transmittance mode) or black & white test-object to provide the similar conditions of registration of images

(reflectance mode).

Pixels
Fig. 9: Image ofthe human hair shaft (left) on the background of the black & white test-object, recorded in the reflectance mode (x 200).
Fig. 10: The typical averaged scans of the hair shaft image for
color components corresponding to three spectral ranges (red.

green, and blue).

Fig. : Image of the human transmission mode (x 200).
hair shaft recorded in the Fig. 12: The typical averaged scans of the hair shaft image for
Using measured transmittance and reflectance and inverse Monte Carlo method, absorption coefficient a and reduced scattering coefficient ofthe hair shaft at three spectral ranges can be estimated (see Table 1).
Table I. Optical properties of different hair shafts obtained by inverse Monte Carlo method. All values were averaged over 30 samples.

. Hair color

Red corn )onent

Pa, 1/CM

14's, 1/cM

Green component

Blue component

P's, 1/CM

P's, i/CM

Black Brown

28.56.3

37.5 18.8

38.67.7

14.5 3.8

1.160.064 0.450.074 0.350.054

40.6 17.4

105.945.1

53.435.6 55.8 29.01

142.371.3 172.242.5 268.383.01

68.38.99

91.391.3

34.82 8.9

2.790.13 1.930.28 1.480.2

90.5 48.3

223.2167.3 229.191.6 331.4 118.2

Lightbrown Blond Grey

1.580.061

233.663.6

0.780.12 0.60.1
The differences between optical properties of various types of hair shafts are well seen. These differences are directly connected with hair shaft structure. High scattering observed for gray hairs is explained by the presence of air-bubbles
within the hair shaft. The different content of melanin granules within various shafts (black, brown, etc) causes
difference in absorption properties. Melanin granules having higher refractive index than surrounding medium (keratin) also give input in light scattering.

Student tasks:

Estimation oftransmittance and reflectance ofdifferent types ofhuman hair shafts using their digital images;
2. Estimation ofabsorption and reduced scattering coefficients ofthe human hair shafts; 3. Analysis ofspectral dependence ofthe absorption and reduced scattering coefficients; 4. Explanation ofthe differences between optical properties ofdifferent types ofhair shafts types on the basis of their morphology.
6. SPATIAL-RESOLVED MICROSPECTROPHOTOMETER FOR TISSUE OPTICAL PROPERTIES AND GEOMETRY STUDIES: CCD TESTER
The optical scheme ofspatial-resolved microspectrophotometer for tissue optical properties and geometry studies: CCD tester is presented in Fig. 1. Object under study is placed in the object plane ofthe imaging lens (microscope objective with magnification equal to 8 and numerical aperture equal to 0.20) and is illuminated by a fiber-optic illuminator (cross-section diameter is equal to 6 mm) assembled with interference filters (bandwidth centered at 600, 700 or 800 nm). Prism is used to change the optical axis direction. Image of the part of the object is formed on the photosensitive area ofthe black & white spectral CCD camera (Electrim 1000). Camera operation is supported by the special software developed by camera producer Electrim Inc. This software allows one to save images ofthe object under study in 8bit bitmap format. Saved image can be processed by the special MathCad (MathSoft Inc., USA) program allows one to find 2D distributions of the object transmittance for selected wavelength (600, 700 or 800 nm) and to measure its geometrical parameters. For example, for given number ofpixels in rows and columns ofCCD chip (192x165 for noninterlace mode) the number ofpixels in the transverse direction ofthe hair shaft image is approximately equal to 35 (for 50-un hair diameter). To measure the hair diameter preliminary calibration by using precision 50-tm grid on the glass substrate is applied.

I CCL) camera (Electrirn.1000)

Fiber-optics illuminator

Fig. I 3 : Optical scheme of spatial-resolved microspectrophotometer for tissue optical properties and geometry studies: CCD tester
Fig. 14: The CCD image ofthe hair shaft.
Fig. 15: The transverse distribution ofhair shaft transmittance.
To define transmittance of an object the ratio of intensity of transmitted light in the area of the object's image I, to
intensity of light transmitted out ofthis image 'r reference, can be taken. In addition the background signal defined by
the dark current of CCD elements 'h should be subtracted from both hair shaft and reference signals. Thus
transmittance is defined as

T='h'h

The optical density D, absorbance Abs, and attenuation (turbidity) 1u at three wavelengths 600, 700, and 800 nm can be

calculated

D = logT,

Abs =lnT, = Abs/d,

where d is the
object thickness or diameter.
Table 2. Measured and calculated transmission (7),
absorbance (Abs) and attenuation coefficient (1u) for hair shafts and mean square deviations (SD) averaged for 27 samples. Attenuation coefficient (it) was calculated for diameter

d50 tm.

Parameter
CCD, ,1.624 nm 55.98.8 0.610.16

,%=800 nm

71.610.6

2700 nm

60.66.5 0.500.10

,14, cm'

0.330.08
I. To measure geometric parameters ofthe human hair shafts. 2. To measure transmission and calculate absorbance and attenuation coefficient ofthe human hair shafts. 3. To measure erythrocytes size changes at glucose action.

7. CONCLUSION

These practical works enable students: to understand principles of optical heterodyning and digital signal processing; to get an overview of principles and schemes of laser instruments, such as laser Doppler anemometers (LDA), and of dynamic speckles properties; to identify the time correlation-spectral and space correlation approaches in speckle dynamics analysis; to understand the basic principles ofhomodyne photodetection and speckle-interferometry; to get an overview of tissue optical properties; to understand principles of photometry; to analyze spectral images of tissue samples; to obtain knowledge of principles of digital analysis of color image of biological objects; to study technique for measurement of transmittance and reflectance of biological objects using their digital images; to study inverse Monte Carlo method for estimation of tissue optical properties; to estimate optical properties of a tissue by inverse Monte Carlo method and spatial digital image analysis.

ACKNOWLEDGMENTS

Some of presented results were received during researches supported by CRDF grant REC-006 and the Russian Basic Research Foundation grant #00-15-96667, "Leading Scientific Schools."

REFERENCES

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