Contrast enhancement using Mie spectra representation for spectroscopic optical coherence tomography

Inverse spectroscopic optical coherence tomography (IS-OCT) for characterization of particle size and concentration

“…Researchers have applied this linear problem formulation to IS-OCT using several different parameters: in Ref. [20], the diameters of microspheres were estimated from spectral interferogram data, Eqn. 2, and a coefficient matrix that was populated with Mie spectra for different diameter particles each evaluated across different depths; in Ref.…”

“…Using the depth dependent spectra, as in Ref. [26], permits incoherent averaging of multiple data sets to reduce speckle [35] without loss of signal amplitude -which can occur in the spectral interferogram method [20] if phase instability is present in the spectra, as is common in some wavelength-swept lasers.…”

“…In optical coherence tomography (OCT), low coherence spectroscopy (LCS) and low coherence interferometry (LCI), light from a low coherence source interact with a sample and a Michelson interferometer is used to extract depth-dependent information about the sample from the backscattered light [9]. In spectroscopic OCT (S-OCT) and LCS, broadband illumination and spectrally sensitive signal detection allows for characterisation of spectrally resolved absorption and scattering properties [6] which have been used to quantify media composition from absorption [10][11][12][13][14] and, when combined with Mie scattering models, to quantify particle size [4,5,[14][15][16][17][18][19][20][21]. The use of inverse problem approaches to analyse particle size distribution in a sample is prevalent in systems using forward-scattering of light (see for example: [22,23]) but is less common in backscattered light techniques such as OCT where it is known as inverse S-OCT (IS-OCT) [19,20,[24][25][26] In this paper, we briefly review the theory of S-OCT to show where each of the existing IS-OCT techniques are derived from [19,20,[24][25][26] before extending the technique presented in [26], that used Lambert-Beer's law to describe the time frequency distributions, to backscattering spectra from Mie theory.…”

“…Where these earlier techniques have demonstrated capability in estimating particle size [19,20,[24][25][26], the technique presented here provides a quantitative estimate of particle size and concentration. Results are presented from data acquired on solutions of polystyrene microspheres with mean diameters of 0.17, 1.04 and 8.91 µm at concentrations of 0.156, 0.625 and 2.5 volume %.…”

Correlation of the derivative as a robust estimator of scatterer size in optical coherence tomography (OCT) [Invited]

“…Most of the methods proposed have been based on the assumption that epithelial cell nuclei can be considered as spheroidal scatterers whose interactions with light are described by Mie theory [11,12]. One approach, to get their nuclear size, has been to curve-fit the backscattered spectra, obtained from the OCT or LCI signal, to the theoretical prediction curves [13][14][15]. The drawback of these methods is that they require an exhaustive search through many possible scattering sizes and precise knowledge of the refractive index of the scatterer and the surrounding medium [16].…”