Mie scatter corrections in single cell infrared microspectroscopy

Konevskikh, Tatiana; Lukács, Rozália; Blümel, R.; Ponossov, Arkadi; Köhler, Achim

doi:10.1039/c5fd00171d

Cited by 42 publications

(55 citation statements)

References 17 publications

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“…The EMSC model estimates the apparent absorbance spectrum in a forward model according to

A_{app} ((), \overset{false˜}{ν}) = b_{k} Z_{ref, k} ((), \overset{false˜}{ν}) + c_{k} + \sum_{i = 1}^{A_{opt}} g_{i, k} p_{i, k} ((), \overset{false˜}{ν}) + ε_{k} ((), \overset{false˜}{ν}),

where b is a parameter taking into account the scaling of the effective optical path length, which results in multiplicative scaling effects, c is a parameter modeling the constant baseline, the sum

\sum_{i = 1}^{A_{opt}} g_{i, k} p_{i, k} ((), \overset{false˜}{ν})

contains scatter effects, which are represented as the PCs

p_{i, k} ((), \overset{false˜}{ν})

of a meta Mie model and corresponding parameters g i , k and

Z_{ref, k} ((), \overset{false˜}{ν})

is the reference spectrum. The index k denotes the iteration k .…”

Section: Theorymentioning

confidence: 99%

“…The next estimate of the imaginary part of the refractive index

n^{'} ((), \overset{false˜}{ν})

is then obtained according to Eq. as

{n^{'}}_{k + 1} ((), \overset{false˜}{ν}) = \frac{A_{corr, k + 1} ((), \overset{false˜}{ν}) ln ((), 10)}{4 π d_{eff} \overset{ν}{true}},

and next estimate of the real part of the refractive index

n_{k + 1} ((), \overset{false˜}{ν})

is obtained by the Kramers‐Kronig transform of the imaginary part of the refractive index

{n^{'}}_{k + 1} ((), \overset{false˜}{ν})

. The next iteration of the reference spectrum

Z_{ref} ((), \overset{false˜}{ν})

is defined as

Z_{ref, k + 1} ((), \overset{false˜}{ν}) = A_{corr, k + 1} ((), \overset{false˜}{ν}) .

…”

Section: Theorymentioning

confidence: 99%

“…. By applying the Hilbert transform to the imaginary part of the refractive index spectrum

n_{s}^{'} ((), \overset{false˜}{ν}),

the real part

n_{italickk, s} ((), \overset{false˜}{ν})

of the refractive index is calculated according to

n_{italickk, s} ((), \overset{false˜}{ν}) = \frac{2}{π} P \int_{0}^{\infty} \frac{s \cdot n_{s}^{'} ((), \overset{false˜}{ν})}{s^{2} - {\overset{false˜}{ν}}^{2}} normald s = \frac{1}{π} P \int_{- \infty}^{\infty} \frac{n_{s}^{'} ((), \overset{false˜}{ν})}{s - \overset{ν}{true}} normald s .

…”

Section: Theorymentioning

confidence: 99%

“…Based on these parameter ranges, we calculate the parameters α 0 and γ according to :

α_{0} = 4 italicπa ((), n_{0} - 1),

γ = \frac{ln ((), 10)}{4 π d_{eff} ((), n_{0} - 1)} .

…”

Section: Theorymentioning

confidence: 99%

See 3 more Smart Citations

An improved algorithm for fast resonant Mie scatter correction of infrared spectra of cells and tissues

Konevskikh

Lukács

Köhler

2017

Journal of Biophotonics

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Mie scattering effects create serious problems for the interpretation of Fourier-transform infrared spectroscopy spectra of single cells and tissues. During recent years, different techniques were proposed to retrieve pure absorbance spectra from spectra with Mie distortions. Recently, we published an iterative algorithm for correcting Mie scattering in spectra of single cells and tissues, which we called "the fast resonant Mie scatter correction algorithm." The algorithm is based on extended multiplicative signal correction (EMSC) and employs a meta-model for a parameter range of refractive index and size parameters. In the present study, we suggest several improvements of the algorithm. We demonstrate that the improved algorithm reestablishes chemical features of the measured spectra, and show that it tends away from the reference spectrum employed in the EMSC. We suggest strategies for choosing parameter ranges and other model parameters such as the number of principal components of the meta-model and the number of iterations. We demonstrate that the suggested algorithm optimizes an error function of the refractive index in a forward Mie model. We suggest a stop criterion for the iterative algorithm based on the error function of the forward model.

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“…The EMSC model estimates the apparent absorbance spectrum in a forward model according to

A_{app} ((), \overset{false˜}{ν}) = b_{k} Z_{ref, k} ((), \overset{false˜}{ν}) + c_{k} + \sum_{i = 1}^{A_{opt}} g_{i, k} p_{i, k} ((), \overset{false˜}{ν}) + ε_{k} ((), \overset{false˜}{ν}),

where b is a parameter taking into account the scaling of the effective optical path length, which results in multiplicative scaling effects, c is a parameter modeling the constant baseline, the sum

\sum_{i = 1}^{A_{opt}} g_{i, k} p_{i, k} ((), \overset{false˜}{ν})

contains scatter effects, which are represented as the PCs

p_{i, k} ((), \overset{false˜}{ν})

of a meta Mie model and corresponding parameters g i , k and

Z_{ref, k} ((), \overset{false˜}{ν})

is the reference spectrum. The index k denotes the iteration k .…”

Section: Theorymentioning

confidence: 99%

“…The next estimate of the imaginary part of the refractive index

n^{'} ((), \overset{false˜}{ν})

is then obtained according to Eq. as

{n^{'}}_{k + 1} ((), \overset{false˜}{ν}) = \frac{A_{corr, k + 1} ((), \overset{false˜}{ν}) ln ((), 10)}{4 π d_{eff} \overset{ν}{true}},

and next estimate of the real part of the refractive index

n_{k + 1} ((), \overset{false˜}{ν})

is obtained by the Kramers‐Kronig transform of the imaginary part of the refractive index

{n^{'}}_{k + 1} ((), \overset{false˜}{ν})

. The next iteration of the reference spectrum

Z_{ref} ((), \overset{false˜}{ν})

is defined as

Z_{ref, k + 1} ((), \overset{false˜}{ν}) = A_{corr, k + 1} ((), \overset{false˜}{ν}) .

…”

Section: Theorymentioning

confidence: 99%

“…. By applying the Hilbert transform to the imaginary part of the refractive index spectrum

n_{s}^{'} ((), \overset{false˜}{ν}),

the real part

n_{italickk, s} ((), \overset{false˜}{ν})

of the refractive index is calculated according to

n_{italickk, s} ((), \overset{false˜}{ν}) = \frac{2}{π} P \int_{0}^{\infty} \frac{s \cdot n_{s}^{'} ((), \overset{false˜}{ν})}{s^{2} - {\overset{false˜}{ν}}^{2}} normald s = \frac{1}{π} P \int_{- \infty}^{\infty} \frac{n_{s}^{'} ((), \overset{false˜}{ν})}{s - \overset{ν}{true}} normald s .

…”

Section: Theorymentioning

confidence: 99%

“…Based on these parameter ranges, we calculate the parameters α 0 and γ according to :

α_{0} = 4 italicπa ((), n_{0} - 1),

γ = \frac{ln ((), 10)}{4 π d_{eff} ((), n_{0} - 1)} .

…”

Section: Theorymentioning

confidence: 99%

See 2 more Smart Citations

An improved algorithm for fast resonant Mie scatter correction of infrared spectra of cells and tissues

Konevskikh

Lukács

Köhler

2017

Journal of Biophotonics

Self Cite

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show abstract

“…[2][3][4][5][6]13,19,30,31,38] as a witness of our progressing understanding of this phenomenon which modifies the shape of the spectra with respect to their pure absorbance counterparts. Scattering occurs when the refractive index varies within the samples, which is already the case within a cell where organelles have their own optical properties.…”

Section: Scattering Effectsmentioning

confidence: 99%

Infrared imaging in histopathology: Is a unified approach possible?

Goormaghtigh

2017

BSI

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Abstract.BACKGROUND: infrared imaging has emerged as a new promising tool in histopathology to provide label free analysis of tissue sections. Interestingly, infrared imaging has the potential to measure many markers at the same time, on one section, without staining. It has been demonstrated to deliver accurate results in numerous cancer pathologies. Yet, today, it is not used in routine diagnostics. The gap between the demonstrated potential and the applications is striking. The reasons why FTIR imaging is not used in the clinics are multiple but one of them is a major obstacle: the diversity of sample preparation, image recording parameters and pre-analytical methods used by the different research groups. This diversity prevents comparison of data and thereby the large scale validation necessary to enter the medical world. OBJECTIVE: we will briefly review here the main aspects of data acquisition and processing used in infrared imaging of tissue sections for which a common approach should be considered. RESULTS: considering requirement for spectral histopathology, the development of the technology and the literature on this topic, guidelines ruling sample preparation and pre-analytical methods do emerge. CONCLUSIONS: consensus values are proposed for most parameters whose current diversity prevents the exchange of data among institutions and thereby the validation of the method on a large scale.

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The Bouguer‐Beer‐Lambert Law: Shining Light on the Obscure

2020

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The Beer‐Lambert law is unquestionably the most important law in optical spectroscopy and indispensable for the qualitative and quantitative interpretation of spectroscopic data. As such, every spectroscopist should know its limits and potential pitfalls, arising from its application, by heart. It is the goal of this work to review these limits and pitfalls, as well as to provide solutions and explanations to guide the reader. This guidance will allow a deeper understanding of spectral features, which cannot be explained by the Beer‐Lambert law, because they arise from electromagnetic effects/the wave nature of light. Those features include band shifts and intensity changes based exclusively upon optical conditions, i. e. the method chosen to record the spectra, the substrate and the form of the sample. As such, the review will be an essential tool towards a full understanding of optical spectra and their quantitative interpretation based not only on oscillator positions, but also on their strengths and damping constants.

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Mie scatter corrections in single cell infrared microspectroscopy

Cited by 42 publications

References 17 publications

An improved algorithm for fast resonant Mie scatter correction of infrared spectra of cells and tissues

An improved algorithm for fast resonant Mie scatter correction of infrared spectra of cells and tissues

Infrared imaging in histopathology: Is a unified approach possible?

The Bouguer‐Beer‐Lambert Law: Shining Light on the Obscure

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