140 4.5  Light Microscopy of Deep or Thick Samples

the aberration due to optical inhomogeneity in thick samples, since corrections for the phase

variations can be made numerically in reciprocal space.

One potential problem is that the detected diffraction pattern consists of just intensity

data and does not contain information concerning the relative phase of a scattered beam

from a particular part of the sample. However, this phase information can be recovered since

the illuminated area moves over the sample to generate redundancy in the data since there

is always some overlap in the sampled regions, which can be used to retrieve the phase from

the scattered object using an algorithm called the “pytchographic iterative engine” (Faulkner

and Rodenburg, 2004).

The main issues with ptychography are the huge volumes of data captured (a gigapixel

image for each illuminated area on the sample) and a requirement for potentially very long

acquisition time scales. A typical single dataset from a static biological sample contains

hundreds of images to obtain sufficient information from different diffraction angles. The

LED array approach improves the time resolution issue to some extent; however, to monitor

any time-​resolved process potentially involves datasets that would fill a normal computer

hard drive very quickly.

4.5.4  MULTIPHOTON EXCITATION

Multiphoton excitation (MPE) is a nonlinear optical effect. In MPE microscopy, the tran­

sition energy required to excite a ground state electron to a higher level during fluores­

cence excitation in a fluorophore can in principle be contributed from the summation of the

equivalent quantum energies of several photons, provided these photons are all absorbed

within a suitably narrow time window. In two-​photon excitation microscopy (or 2PE micros­

copy), the initial excitation of a ground state electron is made following the absorption of two

photons of the same wavelength λ during a time window of only ~10−18 s, since this is the

lifetime of a virtual state halfway between the excited and ground states (Figure 4.4a). This

means that λ is twice that of the required for the equivalent single-​photon excitation process,

and so for visible light, two-​photon excitation fluorescence detection near IR (NIR) incident

wavelengths (~ a micron) are typically used.

Two-​photon absorption, also known as the Kerr effect, is described as a third-​order non­

linear effect because of the dependence of the complex polarization parameter of the optical

medium on the cubic term of the electrical susceptibility. Since two photons are required,

the rate of two-​photon absorption at a depth z depends on the square of the incident photon

intensity I, whereas for one-​photon absorption, the dependence is linear, such that the overall

rate has a quadratic dependence:

(4.20)

d

d

l

z

I

I

= −

+

(

)

α

β 2

where α and β are the one-​ and two-​photon absorption coefficients, respectively.

The longer wavelengths required result is less scattering from biological tissue, for

example, Rayleigh scattering, for which the length scale of the scattering objects is much

smaller than the incident wavelength, has a very sensitive 1/​λ4 dependence. Much of

the scattering in tissue is also due to Mie scattering, that is, from objects of size com­

parable to or greater than λ, for which there is a less sensitive dependence of λ than for

Rayleigh scattering, but still a reduction at higher wavelengths. This is significant since

at depths greater than a few hundred microns, tissues are essentially opaque at visible

light wavelengths due to scattering, whereas they are still optically transparent at the NIR

wavelength used in two-​photon microscopy. The geometrical scattering regime applies to

scattering objects whose effective radius r is at least an order of magnitude greater than the

wavelength of light.

The measure of the ability of an object to scatter can be characterized by its scattering cross-​

section. The cross-​section σ can be deduced from the Mie scattering model for any general