Spectroscopic Optical Coherence Tomography (S-OCT) extracts depth resolved spectra that are inherently available from OCT signals. The back scattered spectra contain useful functional information regarding the sample, since the light is altered by wavelength dependent absorption and scattering caused by chromophores and structures of the sample. Two aspects dominate the performance of S-OCT: (1) the spectral analysis processing method used to obtain the spatially-resolved spectroscopic information and (2) the metrics used to visualize and interpret relevant sample features. In this work, we focus on the second aspect, where we will compare established and novel metrics for S-OCT. These concepts include the adaptation of methods known from multispectral imaging and modern signal processing approaches such as pattern recognition. To compare the performance of the metrics in a quantitative manner, we use phantoms with microsphere scatterers of different sizes that are below the system's resolution and therefore cannot be differentiated using intensity based OCT images. We show that the analysis of the spectral features can clearly separate areas with different scattering properties in multi-layer phantoms. Finally, we demonstrate the performance of our approach for contrast enhancement in bovine articular cartilage.
In this Letter, we present a new approach to processing data from a standard spectral domain optical coherence tomography (OCT) system using depth filtered digital holography (DFDH). Intensity-based OCT processing has an axial resolution of the order of a few micrometers. When the phase information is used to obtain optical path length differences, subwavelength accuracy can be achieved, but this limits the resolvable step heights to half of the wavelength of the system. Thus there is a metrology gap between phase- and intensity-based methods. Our concept addresses this metrology gap by combining DFHD with multiwavelength phase unwrapping. Additionally, the measurements are corrected for aberrations. Here, we present proof of concept measurements of a structured semiconductor sample.
Vitamin D insufficiency is widespread in the northern and partly equatorial hemisphere countries. Fortification of vitamin D in commonly consumed vegetable oils can prevent rickets in children, osteoporosis and bone fractures in adults. Avoiding the loss of vitamin D3 fortification in oils during cooking is beneficial for consumer’s health. The aim of this work was to investigate the stability of cholecalciferol (vitamin D3) fortification in canola oil during baking at 80 to 230°C for 10 to 40 min. The natural antioxidants (β-carotene and α-tocopherol) and the synthetic ones (butylated hydroxytoluene (BHT) and tert-butylhydroquinone (TBHQ)) were used to prevent the degradation of vitamin D3. The kinetic degradation of vitamin D3, oxidative status of canola oil and the bioaccessibility in in vitro digestion were assessed. Vitamin D3 was relatively stable at 80 and 130°C for 10 to 40 min. High temperatures of 180 and 230°C caused the highest loss of vitamin D3 being up to 90%. Reaction rate of vitamin D3 degradation ranged from 2.01 to 6.80 × 10–2 sec–1. BHT and TBHQ had the highest antioxidant activity (> 50 %) to decrease the degradation of vitamin D3 at 230°C. The oxidative status (peroxide value, malondialdehyde content) of canola oil was improved after incorporating antioxidant agents. The vitamin D3 bioaccessibility was increased 1.5 fold after in vitro digestion. The consumption of 5 g brownie containing vitamin D3 100 μg/L and antioxidant agents 180 mg/L in 1 mL of canola oil would cover the daily intake.
We introduce depth-filtered digital holography (DFDH) as a method for quantitative tomographic phase imaging of buried layers in multilayer samples. The procedure is based on the acquisition of multiple holograms for different wavelengths. Analyzing the intensity over wavelength pixel wise and using an inverse Fourier transform leads to a depth-profile of the multilayered sample. Applying a windowed Fourier transform with a narrow window, we choose a depth-of interest (DOI) which is used to synthesize filtered interference patterns that just contain information of this limited depth. We use the angular spectrum method to introduce an additional spatial filtering and to reconstruct the corresponding holograms. After a short theoretical framework we show experimental proof-of-principle results for the method.
Spectroscopic optical coherence tomography (OCT) is an extension of the standard backscattering intensity analysis of OCT. It enables depth resolved monitoring of molecular and structural differences of tissue. One drawback of most methods to calculate the spectroscopic data is the long processing time. Also systematic and stochastic errors make the interpretation of the results challenging. Our approach combines modern signal processing tools with powerful graphics processing unit (GPU) programming. The processing speed for the spectroscopic analysis is nearly 3 mega voxel per second. This allows us to analyze multiple B-Scans in a few seconds and to display the results as a three dimensional data set. Our algorithm contains the following steps in addition to the conventional processing for frequency domain OCT: a quality map to exclude noisy parts of the data, spectral analysis by short time Fourier transform, feature reduction by Principal Component Analysis, unsupervised pattern recognition with K-means and rendering of the gray scale backscattering OCT data which is superimposed with a color map that is based on the results of the pattern recognition algorithm. Our set up provides a spectral range from 650-950nm and is optimized to suppress chromatic errors. In a proof-of-principle attempt, we already achieved additional spectroscopic contrast in phantom samples including scattering microspheres of different sizes and ex vivo biological tissue. This is an important step towards a system for real time spectral analysis of OCT data, which would be a powerful diagnosis tool for many diseases e.g. cancer detection at an early stage.
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