Marcin R. Strąkowski

Quantitative comparison of analysis methods for spectroscopic optical coherence tomography: comment

In a recent paper by Bosschaart et al. [Biomed. Opt. Express 4, 2570 (2013)] various algorithms of time-frequency signal analysis have been tested for their performance in blood analysis with spectroscopic optical coherence tomography (sOCT). The measurement of hemoglobin concentration and oxygen saturation based on blood absorption spectra have been considered. Short time Fourier transform (STFT) was found as the best method for the measurement of blood absorption spectra. STFT was superior to other methods, such as dual window Fourier transform. However, the algorithm proposed by Bosschaart et al. significantly underestimates values of blood oxygen saturation. In this comment we show that this problem can be solved by thorough design of STFT algorithm. It requires the usage of a non-gaussian shape of STFT window that may lead to an excellent reconstruction of blood absorption spectra from OCT interferograms. Our study shows that sOCT can be potentially used for estimating oxygen saturation of blood with the accuracy below 1% and the spatial resolution of OCT image better than 20 μm.

Multilayered structures examination using polarization sensitive optical coherence tomography

The paper presents the way that colour can serve solving the problem of calibration points indexing in a camera geometrical calibration process. We propose a technique in which indexes of calibration points in a black-and-white chessboard are represented as sets of colour regions in the neighbourhood of calibration points. We provide some general rules for designing a colour calibration chessboard and provide a method of calibration image analysis. We show that this approach leads to obtaining better results than in the case of widely used methods employing information about already indexed points to compute indexes. We also report constraints concerning the technique. Nowadays we are witnessing an increasing need for camera geometrical calibration systems. They are vital for such applications as 3D modelling, 3D reconstruction, assembly control systems, etc. Wherever possible, calibration objects placed in the scene are used in a camera geometrical calibration process. This approach significantly increases accuracy of calibration results and makes the calibration data extraction process easier and universal. There are many geometrical camera calibration techniques for a known calibration scene [1]. A great number of them use as an input calibration points which are localised and indexed in the scene. In this paper we propose the technique of calibration points indexing which uses a colour chessboard. The presented technique was developed by solving problems we encountered during experiments with our earlier methods of camera calibration scene analysis [2]-[3]. In particular, the proposed technique increases the number of indexed points points in case of local lack of calibration points detection. At the beginning of the paper we present a way of designing a chessboard pattern. Then we describe a calibration point indexing method, and finally we show experimental results. A black-and-white chessboard is widely used in order to obtain sub-pixel accuracy of calibration points localisation [1]. Calibration points are defined as corners of chessboard squares. Assuming the availability of rough localisation of these points, the points can be indexed. Noting that differences in distances between neighbouring points in calibration scene images differ slightly, one of the local searching methods can be employed (e.g. [2]). Methods of this type search for a calibration point to be indexed, using a window of a certain size. The position of the window is determined by a vector representing the distance between two previously indexed points in the same row or column. However, experiments show that this approach has its disadvantages, as described below. * E-mail: A.Nowakowski@ire.pw.edu.pl Firstly, there is a danger of omitting some points during indexing in case of local lack of calibration points detection in a neighbourhood (e.g. caused by the presence of non-homogeneous light in the calibration scene). A particularly unfavourable situation is when the local lack of detection effects in the appearance of separated regions of detected calibration points. It is worth saying that such situations are likely to happen for calibration points situated near image borders. Such points are very important for the analysis of optical nonlinearities, and a lack of them can significantly influence the accuracy of distortion modelling. Secondly, such methods may give wrong results in the case of optical distortion with strong nonlinearities when getting information about the neighbouring index is not an easy task. Beside this, the methods are very sensitive to a single false localisation of a calibration point. Such a single false localisation can even result in false indexing of a big set of calibration points. To avoid the above-mentioned problems, we propose using a black-and-white chessboard which contains the coded index of a calibration point in the form of colour squares situated in the nearest neighbourhood of each point. The index of a certain calibration point is determined by colours of four nearest neighbouring squares (Fig.1). An order of squares in such foursome is important. Because the size of a colour square is determined only by the possibility of correct colour detection, the size of a colour square can be smaller than the size of a black or white square. The larger size of a black or white square is determined by the requirements of the exact localisation step which follows the indexing of calibration points [3]. In this step, edge information is extracted from a blackand-white chessboard. This edge information needs larger Artur Nowakowski, Wladyslaw Skarbek Institute of Radioelectronics, Warsaw University of Technology, Nowowiejska 15/19, 00-665 Warszawa, A.Nowakowski@ire.pw.edu.pl Received February 10, 2009; accepted March 27, 2009; published March 31, 2009 http://www.photonics.pl/PLP

Spectral measurement of birefringence using particle swarm optimization analysis.

Measurement of birefringence is useful for the examination of technical and biological objects. One of the main problems, however, is that the polarization state of light in birefringent media changes periodically. Without knowledge of the period number, the birefringence of a given medium cannot be reliably determined. We propose to analyze the spectrum of light in order to determine the birefringence. We use a particle swarm optimization algorithm for an automatic processing spectra of light transmitted through birefringent material for two orthogonal states of polarization. We have tested the described algorithm on a liquid crystal cell with varying effective birefringence. The proposed method can be used for the measurement of uniaxial positive birefringence without knowing the number of retardation periods or an approximate value of the measurement result. This fact makes the proposed method useful for automatic measurements, when hundreds or thousands of spectra need to be analyzed.

Time-frequency analysis in optical coherence tomography for technical objects examination

Optical coherence tomography (OCT) is one of the most advanced optical measurement techniques for complex structure visualization. The advantages of OCT have been used for surface and subsurface defect detection in composite materials, polymers, ceramics, non-metallic protective coatings, and many more. Our research activity has been focused on timefrequency spectroscopic analysis in OCT. It is based on time resolved spectral analysis of the backscattered optical signal delivered by the OCT. The time-frequency method gives spectral characteristic of optical radiation backscattered or backreflected from the particular points inside the tested device. This provides more information about the sample, which are useful for further analysis. Nowadays, the applications of spectroscopic analysis for composite layers characterization or tissue recognition have been reported. During our studies we have found new applications of spectroscopic analysis. We have used this method for thickness estimation of thin films, which are under the resolution of OCT. Also, we have combined the spectroscopic analysis with polarization sensitive OCT (PS-OCT). This approach enables to obtain a multiorder retardation value directly and may become a breakthrough in PS-OCT measurements of highly birefringent media. In this work, we present the time-frequency spectroscopic algorithms and their applications for OCT. Also, the theoretical simulations and measurement validation of this method are shown.

Dispersion compensation in optical coherence tomography

Dispersion of optical elements and sample in optical coherence tomography (OCT) system introduce a wavelength dependent phase distortion to the light beam propagating in OCT system. This causes blurring of the image in high resolution OCT using broadband light sources. Also decreased resolution with the depth of a sample is observed. To avoid this, the overall dispersion of the system can be compensated using a dispersive material in the reference arm of a system. Unfortunately, the dispersion is changed in the system with the probing depth. Overcome to this problem is numerical dispersion compensation technique. Calculations can be made after the measurements have been taken to provide depth dependent compensation. Various techniques and their possibilities are presented.

Optical Coherence Tomography for nanoparticles quantitative characterization

The unique features of nanocomposite materials depend on the type and size of nanoparticles, as well as their placement in the composite matrices. Therefore the nanocomposites manufacturing process requires inline control over certain parameters of nanoparticles such as dispersion and concentration. Keeping track of nanoparticles parameters inside a matrix is currently a difficult task due to lack of a fast, reliable and cost effective way of measurement that can be used for large volume samples. For this purpose the Optical Coherence Tomography (OCT) has been used. OCT is an optical measurement method, which is a non-destructive and non-invasive technique. It is capable of creating tomographic images of inner structure by gathering depth related backscattered signal from scattering particles. In addition, it can analyse, in a single shot, area of the centimetre range with resolution up to single micrometres. Still to increase OCT measurement capabilities we are using additional system extensions such as Spectroscopic OCT (SOCT). With such addition, we are able to measure depth related parameters such as scattering spectra and intensity of backscattered signal. Those parameters allow us to quantitatively estimate nanoparticles concentration. Gaining those, information allows to calculate volume concentration of nanoparticles. In addition, we analyse metallic oxides nanoparticles. To fully characterize nanoparticles it is necessary to find and differentiate those that are single particles from agglomerated ones. In this contribution we present our research results on using the LCI based measurement techniques for evaluation of materials with nanoparticles. The laboratory system and signal processing algorithms are going to be shown in order to express the usefulness of this method for inline constant monitoring of the nanocomposite material fabrication.

Spectroscopic analysis for polarization sensitive optical coherent tomography

The paper presents the way that colour can serve solving the problem of calibration points indexing in a camera geometrical calibration process. We propose a technique in which indexes of calibration points in a black-and-white chessboard are represented as sets of colour regions in the neighbourhood of calibration points. We provide some general rules for designing a colour calibration chessboard and provide a method of calibration image analysis. We show that this approach leads to obtaining better results than in the case of widely used methods employing information about already indexed points to compute indexes. We also report constraints concerning the technique. Nowadays we are witnessing an increasing need for camera geometrical calibration systems. They are vital for such applications as 3D modelling, 3D reconstruction, assembly control systems, etc. Wherever possible, calibration objects placed in the scene are used in a camera geometrical calibration process. This approach significantly increases accuracy of calibration results and makes the calibration data extraction process easier and universal. There are many geometrical camera calibration techniques for a known calibration scene [1]. A great number of them use as an input calibration points which are localised and indexed in the scene. In this paper we propose the technique of calibration points indexing which uses a colour chessboard. The presented technique was developed by solving problems we encountered during experiments with our earlier methods of camera calibration scene analysis [2]-[3]. In particular, the proposed technique increases the number of indexed points points in case of local lack of calibration points detection. At the beginning of the paper we present a way of designing a chessboard pattern. Then we describe a calibration point indexing method, and finally we show experimental results. A black-and-white chessboard is widely used in order to obtain sub-pixel accuracy of calibration points localisation [1]. Calibration points are defined as corners of chessboard squares. Assuming the availability of rough localisation of these points, the points can be indexed. Noting that differences in distances between neighbouring points in calibration scene images differ slightly, one of the local searching methods can be employed (e.g. [2]). Methods of this type search for a calibration point to be indexed, using a window of a certain size. The position of the window is determined by a vector representing the distance between two previously indexed points in the same row or column. However, experiments show that this approach has its disadvantages, as described below. * E-mail: A.Nowakowski@ire.pw.edu.pl Firstly, there is a danger of omitting some points during indexing in case of local lack of calibration points detection in a neighbourhood (e.g. caused by the presence of non-homogeneous light in the calibration scene). A particularly unfavourable situation is when the local lack of detection effects in the appearance of separated regions of detected calibration points. It is worth saying that such situations are likely to happen for calibration points situated near image borders. Such points are very important for the analysis of optical nonlinearities, and a lack of them can significantly influence the accuracy of distortion modelling. Secondly, such methods may give wrong results in the case of optical distortion with strong nonlinearities when getting information about the neighbouring index is not an easy task. Beside this, the methods are very sensitive to a single false localisation of a calibration point. Such a single false localisation can even result in false indexing of a big set of calibration points. To avoid the above-mentioned problems, we propose using a black-and-white chessboard which contains the coded index of a calibration point in the form of colour squares situated in the nearest neighbourhood of each point. The index of a certain calibration point is determined by colours of four nearest neighbouring squares (Fig.1). An order of squares in such foursome is important. Because the size of a colour square is determined only by the possibility of correct colour detection, the size of a colour square can be smaller than the size of a black or white square. The larger size of a black or white square is determined by the requirements of the exact localisation step which follows the indexing of calibration points [3]. In this step, edge information is extracted from a blackand-white chessboard. This edge information needs larger Artur Nowakowski, Wladyslaw Skarbek Institute of Radioelectronics, Warsaw University of Technology, Nowowiejska 15/19, 00-665 Warszawa, A.Nowakowski@ire.pw.edu.pl Received February 10, 2009; accepted March 27, 2009; published March 31, 2009 http://www.photonics.pl/PLP

Gold nanoparticles evaluation using functional optical coherence tomography

The main object of this research was to assess the ability to characterize the gold nanoparticles using optical modalities like optical coherence tomography. Since the nanoparticles, especially gold one, have been very attractive for medical diagnosis and treatment the amount of research activities have been growing rapidly. The nanoparticles designed for different applications like contrast agents or drugs delivery change the optical features of tissue in different way. Therefore, the expanded analysis of scattering optical signal may lead to obtain much more useful information about the tissues health and the treatment efficiency. The noninvasive measurements of the concentration and distribution of the nanoparticles, as well as their size in the media have been taken under consideration. For this purpose the polarization sensitive optical coherence tomography system with spectroscopic analysis (PS-SOCT) has been designed and used. In this contribution we are going to present the PS-SOCT measurement data obtained for the gold nanoparticles. The measurements have been taken for the liquid (gold nanoparticles in water) samples changing the particles concentrations in time.

Nanoparticles displacement analysis using optical coherence tomography

Optical coherence tomography (OCT) is a versatile optical method for cross-sectional and 3D imaging of biological and non-biological objects. Here we are going to present the application of polarization sensitive spectroscopic OCT system (PS-SOCT) for quantitative measurements of materials containing nanoparticles. The PS-SOCT combines the polarization sensitive analysis with time-frequency analysis. In this contribution the benefits of using the combination of timefrequency and polarization sensitive analysis are being expressed. The usefulness of PS-SOCT for nanoparticles evaluation is going to be tested on nanocomposite materials with TiO2 nanoparticles. The OCT measurements results have been compared with SEM examination of the PMMA matrix with nanoparticles. The experiment has proven that by the use of polarization sensitive and spectroscopic OCT the nanoparticles dispersion and size can be evaluated.

Efficient signal processing in spectroscopic optical coherence tomography

Spectroscopic optical coherence tomography (SOCT) is an extension of a standard OCT technique, which allows to obtain depth-resolved, spectroscopic information on the examined sample. It can be used as a source of additional contrast in OCT images e.g. by encoding certain features of the light spectrum into the hue of the image pixels. However, SOCT require computation of time-frequency distributions of each OCT A-scan, what is a very time consuming procedure. This is particularly important in a real-time OCT imaging. Here, we present a new approach to SOCT signal processing that allows for nearly tenfold reduction of a required computation time. The presented approach is based on a recursive analysis of OCT scan in time-domain without necessity of computing neither short-time Fourier transform or any other time-frequency distribution.