Ординатура / Офтальмология / Английские материалы / Handbook of Optical Coherence Tomography_Bouma, Tearney_2002
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12.6.3 Supplementation by Optical Coherence Profilometry
In addition to OCT measurements of the morphological structure of the skin, clinically relevant data about alterations of the skin can be acquired by measurements of the surface skin topology. Alterations in the surface can also be detected by low coherence interferometry. We call this method optical coherence profilometry (OCP) [4] or coherence radar [28]. For in vivo OCP on human skin we use fiber-optic coherence radar [18,27].
The experimental setup for coherence radar uses a Michelson interferometer (Fig. 12). The light source is a light-emitting diode (LED). The reference mirror and the skin are illuminated by a plane wave. Light scattered back from the surface of the skin is imaged onto the CCD camera. Imaging with a finite aperture causes speckle in the image plane. Each speckle has a constant but arbitrary phase. Therefore, the speckles are the actual signal carrier in interferometry on rough surfaces [28].
White light interference displays maximum contrast in a plane, where the object optical pathlength is equal to the reference pathlength. To get the 3-D shape, the reference plane has to be scanned through the object. During the scan, within each pixel of the CCD camera an intensity variation occurs, called a correlogram. Its period is one-half of the average wavelength of the light source. For each pixel the contrast of the correlogram is measured during the scan. The maximum contrast defines the locus of equal optical pathlengths. Outside the center of the correlogram, the interference contrast decays rapidly, dependent on the coherence length of the light source. Special hardware is used to detect this maximum and to save the actual position of the translation stage. This is done for each of the 256,000 pixels in parallel. The speed of depth measurement is vs ¼ =6T, which is 4 m/s using a standard video camera with a 25 Hz frame rate. By modification of the sensor, the speed can be increased to 70 m=s [29].
The measuring uncertainty z (standard deviation) of measurements with continuous coherence radar is caused by the statistical phase in the speckle. Therefore z is mainly limited by the roughness of the object and not by parameters of the sensor (e.g., observation aperture). Industrial surfaces can be measured with z < 1 m [28].
The algorithm is based on measuring the contrast of the correlogram, not its phase. Therefore movements of the object leading to distortions of the phase will not influence the contrast. This is why in vivo measurements of a slightly moving object such as human skin are possible.
The conventional setup for coherence radar, developed for technical objects, is fixed on a bulky translation stage. The part of the human body to be measured has to be brought to the sensor. This limits the flexibility of the system. Therefore we implemented a fiber-optic version of coherence radar with a translation stage separated from the sensor head [18,27].
For the separation of the translation stage from the sensor head, a fiber has to be used in the reference arm of the interferometer (Fig. 13). To ensure equal optical pathlengths in the object and reference arms, a second fiber has to be placed into the object arm. This is done by inserting an additional beamsplitter (BS1 in Fig. 13), which splits the incoming light up into reference and object beams before the main beamsplitter of the coherence radar (BS2 in Fig. 13) is reached. This setup is equivalent to a combination of a Mach–Zehnder interferometer and a Michelson interferometer. The scan in the z-direction is done in the reference arm of the Mach–
Figure 12
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(a) Experimental setup for conventional coherence radar. (b) Correlogram of an in vivo measurement of human skin.
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Figure 13 Setup for fiber-optic coherence radar.
Zehnder interferometer by varying the optical pathlength between the two collimators CR1 and CR2. Because the sensor head contains no mechanical moving parts, it can be miniaturized and becomes mobile.
Figure 14 illustrates the fiber-optic implementation of coherence radar. The sensor consists of two spatially separated components: the sensor head and a module containing the translation stage. The two parts are connected by single-mode fibers. The light source is an SLD. An additional pilot laser in the visible range is used for aiming.
Figure 14 Fiber-optic implementation of coherence radar.
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Figure 15 Mobile sensor head of the coherence radar instrument.
The sensor head contains the main part of the coherence radar for in vivo OCP. A beamsplitter superimposes the parallel reference beam with the light scattered back from the surface of the skin (Figs. 14 and 15). The measurable area of the skin surface depends on the output power of the light source and on the reflectivity of the surface. Presently the field of view is 5 mm 5 mm.
In vivo OCP measurements of several regions of the body—i.e., hand, forearm, nose, belly, etc.—have been performed [27]. Figure 16 displays two gray-level- encoded height maps of measurements. The field of view is 2:5 mm 2:5 mm. Both measurements were performed without any preparation of the skin and at a z speed of 4 m=s. At the bottom of Fig. 16 the profile of the surface along the line depicted in the photo above is displayed. The picture to the left shows the wrinkles of the skin of a fingertip, which have a depth of about 80 m. The measurement of the forearm on the right displays a mesh of deep wrinkles (depth of 80 m) and shallow wrinkles (depth of 30 m).
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Figure 16
In vivo OCP measurements with the fiber-optic coherence radar.
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12.7CONCLUSION
Spectral radar is an optical sensor for the acquisition of skin morphology. The scattering amplitude aðzÞ along one vertical axis from the surface into the bulk can be measured within one exposure. No reference arm scanning is necessary. The dynamic range is limited by the maximum power of the object. The more photons from the object contribute to the interference signal, the higher is the dynamic range. The experimental determination of the dynamic range is D ¼ 79 dB. The dynamic range is, for the present implementation, limited by the A/D converter. Spectral radar works in the Fourier domain and has the same advantage over standard (time-domain) OCT as Fourier spectroscopy has over standard spectroscopy: the dynamic range of FDOCT is higher than that of TDOCT. In Table 1, FDOCT and TDOCT are compared ‘‘in a nutshell.’’ We showed optograms of in vivo measurements of human skin obtained with a fiber-optic implementation of the sensor. The thickness of the skin layers at different locations of the body in vivo is accurately displayed. With spectral radar we can distinguish different skin alterations such as malignant melanoma, Bowen’s disease, and skin damage by larva migrane.
In addition to OCT measurements of the morphological structure of the skin, clinically relevant data about alterations of the skin can be acquired by measurements of the surface skin topology. We used fiber-optic coherence radar for in vivo OCP on human skin. The measuring uncertainty on the skin is about 2 m. The field of view is presently 5 mm 5 mm.
ACKNOWLEDGMENT
We acknowledge suggestions and support of the project given by Dr. Hoppe of Beiersdorf AG and by Prof. Schaefer and Dr. Dauga of l’Ore´al Recherche. We further acknowledge in vivo measurements on patients, interpretation of the results, and valuable suggestions and support by Dr. Kiesewetter of the Dermatologische Universita¨tsklinik und Poliklinik, Erlangen. This chapter was funded by the BMBF, registration 13N7148.
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13
Alternative OCT Techniques
CHRISTOPH K. HITZENBERGER and ADOLF F. FERCHER
University of Vienna, Vienna, Austria
13.1OPTICAL DIFFRACTION TOMOGRAPHY AND OPTICAL COHERENCE TOMOGRAPHY
In optical tomography, the spatial structure of the illuminated object is reconstructed from scattered light data. Because the wavelength of optical radiation is not appreciably smaller than the structural elements of the object to be resolved, diffraction plays an important role. Hence, high resolution optical tomography must be based on diffraction physics. The diffraction projection theorem yields a solution for the corresponding inversion problem and provides the mathematical frame of optical diffraction tomography (ODT) [1]. It states that some of the three-dimen- sional spatial Fourier components of the scattering potential can be determined from measurements of amplitudes and phases of the scattered field [2]. This theorem has been used with many types of radiation in addition to optical radiation [3], for example, with X-rays [4,5] and in ultrasonics [6].
‘‘Tomographic’’ imaging techniques derive two-dimensional data sets from a three-dimensional object to obtain a slice image of the internal structure. In optical coherence tomography (OCT) [7], scattered field data are derived from backscattered light. The depth position of light-remitting sites is detected by a partial coherence interferometric (PCI) depth scan (so-called optical A-scan), whereas lateral positions are determined by scanning the probe beam across the object. Usually, a Michelson interferometer with a short coherence length light source is used to perform the depth scan. The OCT image is synthesized from a series of laterally adjacent PCI depth-scan signals.
The diffraction projection theorem is derived with the assumption of weakly scattering objects. This assumption means that photons are scattered at most once. Hence, the scattered photons carry information about one light-scattering site. In
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this case the scattered field can be obtained by the first Born approximation as a volume integral extended over the illuminated object volume Vðr0Þ [1]. In OCT the object is illuminated by a rather narrow light beam. Therefore, far-field scattering is a reasonable approximation that leads to a simplified version of the diffraction projection theorem [8,9]:
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length, ! is the frequency, c is the velocity of light, and r is the position vector. Foðr) is the scattering potential of the object (we call it the ‘‘object structure’’):
FoðrÞ ¼ k2 mðrÞ2 1 ð2Þ
where mðr) is the complex refractive index of the object. Equation (1) is basically a Fourier transformation. It can easily be understood in terms of Huygens’ principle: The scattered wave (with wave vector kðSÞ) is composed of elementary waves with amplitudes and phases determined by the Fourier transform F^oðK) of the scattering potential of the object [9]. Hence, the three-dimensional scattering potential Foðr) can be obtained by an inverse Fourier transform of the complex amplitude of the scat-
tered field Eoðr; K; tÞ.
However, access to the Fourier data is considerably restricted. That can be seen from the Fourier data geometry in K-space, Fig. 1. For any direction of kðSÞ the scattering vector K points to the surface of the so-called Ewald sphere. As can also been seen from Fig. 1, backscattering with monochromatic light gives access to only one high spatial frequency, i.e., discontinuities of the scattering potential. A wavelength range from 1 to 2 obtains Fourier components of the scattering potential in the spatial frequency range ½K1Z; K2Z& and therefore has access to a finite range of
Figure 1 K-space geometry of backscattering (backscattered light is detected at P). kð1iÞ ¼ wave vector of illuminating wave at wavelength 1; kð1SÞ ¼ wave vector of scattered wave at 1j K1 ¼ scattering vector corresponding to 1; E1; E2 ¼ Ewald spheres corresponding to wavelengths 1 and 2; IB ¼ illuminating beam; BS ¼ Fourier data accessible by backscattering; OB ¼ object.
