Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Finite-Difference Time-Domain simulations of transmission microscopy
  enable a better interpretation of 3D nerve fiber architectures in the brain   In many laboratories, conventional bright-field transmission microscopes are
available to study the structure and organization principles of fibrous tissue
samples, but they usually provide only 2D information. To access the third
(out-of-plane) dimension, more advanced techniques are employed. An example is
3D Polarized Light Imaging (3D-PLI), which measures the birefringence of
histological brain sections to derive the spatial nerve fiber orientations.
Here, we show how light scattering in transmission microscopy measurements can
be leveraged to gain 3D structural information about fibrous tissue samples
like brain tissue. For this purpose, we developed a simulation framework using
finite-difference time-domain (FDTD) simulations and high performance
computing, which can easily be adapted to other microscopy techniques and
tissue types with comparable fibrous structures (e.g., muscle fibers, collagen,
or artificial fibers). As conventional bright-field transmission microscopy
provides usually only 2D information about tissue structures, a
three-dimensional reconstruction of fibers across several sections is
difficult. By combining our simulations with experimental studies, we show that
the polarization-independent transmitted light intensity (transmittance)
contains 3D information: We demonstrate in several experimental studies on
brain sections from different species (rodent, monkey, human) that the
transmittance decreases significantly (by more than 50%) with the increasing
out-of-plane angle of the nerve fibers. Our FDTD simulations show that this
decrease is mainly caused by polarization-independent light scattering in
combination with the finite numerical aperture of the imaging system. This
allows to use standard transmission microscopy techniques to obtain 3D
information about the fiber inclination and to detect steep fibers, without
need for additional measurements.

29
The categories of this paper are: funct-an
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
13
The categories of this paper are: quant-ph
6
The categories of this paper are: astro-ph
11
The categories of this paper are: hep-lat
10
The categories of this paper are: q-bio
5
The categories of this paper are: gr-qc
21
The categories of this paper are: adap-org
12
The categories of this paper are: nucl-th
25
The categories of this paper are: patt-sol
15
The categories of this paper are: nucl-ex
4
The categories of this paper are: cond-mat
37
The categories of this paper are: supr-con
0
The categories of this paper are: hep-ph
9
The categories of this paper are: nlin