FDTD simulation data for Optical Diffraction Tomography

This dataset
contains 2D and 3D complex field sinograms for optical diffraction
tomography created with finite-difference time domain simulations
using Meep (http://ab-initio.mit.edu/wiki/index.php?title=Meep).
The entire complex electric field data from the simulations would
have amounted to >2TB of data which is not easy to share and also
contain a lot of redundant and uninteresting (for tomography at
least) information. Most of these data were used in the ODTbrain
paper (https://dx.doi.org/10.1186/s12859-015-0764-0).

Data Structure

Each dataset is an
HDF5 file (https://www.hdfgroup.org)
that contains the simulation structure (the cell phantom), a
background field (simulation without phantom), and a field for each
rotational position of the phantom (sinogram). The fields are slices
through the complex electrical field in the original simulation
volume behind the phantom at the end of the simulation (supposedly
steady state). The slice position is written as the HDF5 attribute
“extraction focus distance [px]”. The slice position is important
for the reconstruction, because the fields must be numerically
refocused to the center of the simulation volume before
reconstruction. The perfectly matched layer (PML) has already been
cropped from the fields. Alongside each field, the source code of the
Meep simulation and the standard-output of the compiled simulation
are stored. You can also find the simulation templates in the
ODTbrain repository at
https://github.com/RI-imaging/ODTbrain/tree/master/misc.
I recommend you to explore the files using HDFView
(https://www.hdfgroup.org/downloads/hdfview/).

Naming Scheme

I adopted the naming
scheme of the original simulations.

- The first part of
the file name determines the dimension of the simulation. The larger
“phantom_3d” files contain the 3D simulation sinograms.

- “A” is the
total number of angles for which simulations were performed.

- “R” is the
resolution (number of pixels per wavelength).

- “T” is the
total number of simulation steps performed.

- “Nmed” is the
refractive index (RI) of the medium surrounding the cell phantom.

- “Ncyt” is the
RI of the phantom’s cytoplasm.

- “Nnuc” is the
RI of the phantom’s nucleus.

- “Nleo” is the
RI of the phantom’s nucleolus.

The final part of
the file name indicates to which type of study the simulation
belongs:

- “angles”:
varying the total number of acquisition angles

- “step-count”:
varying the total number of time steps

-
“refractive-index”: varying the internal RI values of the cell
phantom

- “size”:
varying the size of the phantom

Getting Started

I added two Python
scripts “recon_2d.py” and “recon_3d.py” (tested with Python
3.9 on Ubuntu 22.04) that will allow you to obtain RI reconstructions
from the 2D and 3D sinograms. For this to work, you will have to
install the Python libraries imported in those scripts. Note that for
the 3D data you can also use the graphical tool CellReel
(https://github.com/RI-imaging/CellReel).