Abstract
Single molecule localization microscopy is a recently developed superresolution imaging technique to visualize structural properties of single cells. The basic principle consists in chemically attaching fluorescent dyes to the molecules, which after excitation with a strong laser may emit light. To achieve superresolution, signals of individual fluorophores are separated in time. In this paper we follow the physical and chemical literature and derive mathematical models describing the propagation of light emitted from dyes in single molecule localization microscopy experiments via Maxwell’s equations. This forms the basis of formulating inverse problems related to single molecule localization microscopy. We also show that the current status of reconstruction methods is a simplification of more general inverse problems for Maxwell’s equations as discussed here.
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Acknowledgements
OS is supported by the Austrian Science Fund (FWF), within SFB F68 (Tomography across the scales), project F6807-N36 (Tomography with Uncertainties) and I3661-N27 (Novel Error Measures and Source Conditions of Regularization Methods for Inverse Problems). KS is supported by the Austrian Science Fund (FWF), project P31053-N32 (Weighted X-ray transform and applications). MLM, MS and GS are also supported by the SFB F68, project F6809-N36 (Ultra-high Resolution Microscopy). JS is supported in part by the NSF grant DMS-1912821 and the AFOSR grant FA9550-19-1-0320.
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Appendices
Appendix 1: Derivation of Particular Fourier Transforms
Before reading through the appendix it might be useful to recall the notation of Table 2. The derivation in Lemma 3 uses the residual theorem.
Theorem 2 (Residual Theorem)
Let the function \(z \in \mathbb {C} \to \tilde {f}(z):=f(z) \mathrm e^{\mathrm i a z}\) with a > 0 satisfy the following properties:
-
1.
f is analytic with at most finitely many poles p i , i = 1, …, m, which do not lie on the real axis.
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2.
There exists M, R > 0 such that for every \(z \in \mathbb {C}\) satisfying ℑ(z) ≥ 0 and \(\left | z\right | \geq R\)
$$\displaystyle \begin{aligned} \left| f(z)\right| \leq \frac{M}{\left| z\right| }. \end{aligned} $$(108)
Then
Using this lemma we are able to prove the following result used in Lemma 3:
Lemma 10
Let the assumptions and notation of Lemma 3 hold (in particular this means that \(r_3, r_3^{\boldsymbol {\Psi }} \in \mathbb {R}\) satisfy \(r_3-r_3^{\boldsymbol {\Psi }} > 0\) ), then
First, we note that
Now, we calculate the Fourier-transform of each of the two terms on the right-hand side. The second term can be calculated from Eq. (9) and is given by
For the calculation of the first term, let
and we use the residual theorem:
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Clearly f is analytic with potential poles at k 3 = ±q ε.
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To verify Eq. (108) we use the elementary calculation rules for ∇r×, summarized in Eq. (45) and get
$$\displaystyle \begin{aligned} ~ & \frac{(\boldsymbol{\Psi} \times \mathbf{k}) \times \mathbf{k}}{ k_3^2 - q_{\varepsilon}^2} =-\frac{1}{ k_3^2 - q_{\varepsilon}^2} \\ &\left(\!\!k_3^2 (\boldsymbol{\Psi} - \Psi_3 {\mathbf{e}}_3) - k_3 \begin{pmatrix} \Psi_3 k_1 \\ \Psi_3 k_2 \\ \Psi_1 k_1 {+} \Psi_2 k_2\end{pmatrix} {+} (k_1^2+k_2^2) \boldsymbol{\Psi} {-} \begin{pmatrix} (\!\Psi_1 k_1 + \Psi_2 k_2)k_1 \\ (\Psi_1 k_1 + \Psi_2 k_2)k_2 \\0 \end{pmatrix} \!\!\right) \\ = &-\frac{1}{k_3^2 - q_{\varepsilon}^2} \left(\!k_3^2 \left( \boldsymbol{\Psi} - \Psi_3 {\mathbf{e}}_3\right) - k_3 \begin{pmatrix} \Psi_3 k_1 \\ \Psi_3 k_2 \\ \Psi_1 k_1 + \Psi_2 k_2\end{pmatrix} \right.\\ &\left. + (k_1^2+k_2^2) \left( \boldsymbol{\Psi} - \Psi_3 {\mathbf{e}}_3\right) + \begin{pmatrix} -\Psi_1 k_1^2 - \Psi_2 k_2k_1 \\ -\Psi_2 k_2^2 - \Psi_1 k_1k_2 \\(k_1^2+k_2^2) \Psi_3 \end{pmatrix} \!\! \right) \\ = &-\frac{1}{ k_3^2 - q_{\varepsilon}^2} \left((k_3^2-q_{\varepsilon}^2) \left( \boldsymbol{\Psi} - \Psi_3 {\mathbf{e}}_3\right) - k_3 \begin{pmatrix} \Psi_3 k_1 \\ \Psi_3 k_2 \\ \Psi_1 k_1 + \Psi_2 k_2\end{pmatrix} + \kappa^2 \left( \boldsymbol{\Psi} - \Psi_3 {\mathbf{e}}_3\right)\right.\\ &\left. + \begin{pmatrix} -\Psi_1 k_1^2 - \Psi_2 k_2k_1 \\ -\Psi_2 k_2^2 - \Psi_1 k_1k_2 \\(k_1^2+k_2^2) \Psi_3 \end{pmatrix} \right) = - \boldsymbol{\Psi} + \Psi_3 {\mathbf{e}}_3 + \frac{k_3}{k_3^2 - q_{\varepsilon}^2} \mathbf{a} - \frac{1}{k_3^2 - q_{\varepsilon}^2} \mathbf{b} \end{aligned} $$where
$$\displaystyle \begin{aligned} \mathbf{a} = \begin{pmatrix} \Psi_3 k_1 \\ \Psi_3 k_2 \\ \Psi_1 k_1 + \Psi_2 k_2\end{pmatrix} \text{ and } \mathbf{b} = \begin{pmatrix} (\kappa^2 - k_1^2) \Psi_1 -\Psi_2 k_1 k_2 \\ (\kappa^2 - k_2^2) \Psi_2 - \Psi_1 k_1 k_2 \\ (k_1^2 + k_2^2)\Psi_3 \end{pmatrix}. \end{aligned}$$Using that
$$\displaystyle \begin{aligned} \frac{k_3}{k_3^2-q_{\varepsilon}^2} = \frac{1}{2} \left(\! \frac{1}{k_3-q_{\varepsilon}} + \frac{1}{k_3+q_{\varepsilon}} \!\right) \text{ and } \frac{1}{k_3^2-q_{\varepsilon}^2} = \frac{1}{2q_{\varepsilon}} \left( \frac{1}{k_3-q_{\varepsilon}} - \frac{1}{k_3+q_{\varepsilon}} \right) \end{aligned}$$we get
$$\displaystyle \begin{aligned} \frac{(\boldsymbol{\Psi} \times \mathbf{k}) \times \mathbf{k}}{ k_3^2 - q_{\varepsilon}^2} + \boldsymbol{\Psi} - \Psi_3 {\mathbf{e}}_3 = \frac{1}{k_3-q_{\varepsilon}} \left( \frac{1}{2} \mathbf{a} - \frac{1}{2q_{\varepsilon}} \mathbf{b} \right) + \frac{1}{k_3+q_{\varepsilon}} \left( \frac{1}{2}\mathbf{a} + \frac{1}{2q_{\varepsilon}} \mathbf{b} \right). \end{aligned} $$(112)This shows Eq. (108).
Therefore we can apply the residual Theorem 2 for f defined in (111). Then, since q ε is complex with positive imaginary part, f has only one pole in the upper half plane, and we get
This implies
Appendix 2: Derivation of the Far Field Approximation for the Electric Field
Lemma 11
Let ζ be the function defined in Eq.(61). That is, for all \({\mathbf {k}}_{12} \in \mathbb {R}^2\) ζ(k 12) = k 12 ⋅v + q(k 12), with \(q = \sqrt {\kappa ^2 - k_1^2 - k_2^2}\) ; note the formal definition of q in Eq.(42) is via the limit ε → 0. Then the gradient of ζ is given by
which vanishes for
Consequently r = r 3 e 3+r 3 ( v1 ) T as in Eq.(59) satisfies
Moreover, with q as defined in Eq.(42), we get the following identities
The Hessian of ζ is given by
which evaluated at \(\hat {\mathbf {k}}\) gives
and the determinant satisfies
Appendix 3: Bessel Identities
For \(x \in \mathbb {R}\) and φ 0 ∈ [0, 2π) the Bessel-identities hold:
where J m is the Bessel function of the first kind of order m.
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Lopez-Martinez, M. et al. (2021). Inverse Problems of Single Molecule Localization Microscopy. In: Kaltenbacher, B., Schuster, T., Wald, A. (eds) Time-dependent Problems in Imaging and Parameter Identification. Springer, Cham. https://doi.org/10.1007/978-3-030-57784-1_12
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DOI: https://doi.org/10.1007/978-3-030-57784-1_12
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