nad_eed_3d(1) General Commands Manual nad_eed_3d(1)
NAME
nad_eed_3d - Nonlinear anisotropic diffusion, edge enhancing, in 3D
SYNOPSIS
nad_eed_3d [options] input_file output_file
DESCRIPTION
nad_eed_3d is Frangakis and Hegerl's 3D anisotropic diffusion program
with edge-enhancing diffusion only (see Frangakis, A., and Hegerl, R.,
2001. "Noise reduction in electron tomographic reconstructions using
nonlinear anisotropic diffusion." J. Struct. Biol. 135: 239-205). In
addition to options to control the algorithm itself, this version pro-
vides some options to make it easier to explore the effects of differ-
ent parameters.
The program requires ~36 times as much memory as the number of voxels
in the input file. To process a large volume, place the command line
needed to run the program into a command file and use chunksetup to
obtain command files to process the volume in chunks. Determine the
maximum number of megabytes of memory that you want this processing to
require, and divide by 36 to obtain the value to enter with the -m
option to chunksetup. See the example below.
Finding the right parameters for anisotropic diffusion can be diffi-
cult. To adjust parameters, first clip out a small subvolume, e.g.,
100x100x30 pixels, with typical features of interest. One strategy is
to look at a restricted range of iterations, such as 5-10 or possibly
5-15, and find the K value that gives the desired result. A very wide
range of K needs to be explored, perhaps from .02 to 5 times the stan-
dard deviation of the data. For typical byte data this might be a
range of 0.4 to 100. The range should thus be explored in two stages.
In the first stage, you might try K values of 0.4, 1.6, 6.4, 26, 102,
then look at the results as described below. When you see that the
desired K value falls in one of these intervals, then try 5 K values to
fill in the interval with finer steps, such as 2.4, 3.2, 4.0, 4.8, and
5.6 for the interval from 1.6 and 6.4. Once you have chosen your
parameters, you can process the whole volume.
The Etomo program contains an interface for extracting a subvolume,
testing different K values and iteration numbers, and running the dif-
fusion on a full volume. From the File menu, select "New Parallel
Process" then press the "Nonlinear Anisotropic Diffusion" button.
OPTIONS
-k value
The K value (sometimes referred to as lambda). The ratio of the
local image gradient to K is used to determine whether density
will diffuse isotropically or primarily in the direction of
least density variation (along edges). Lower K values will pre-
serve more edges; higher K values will give more isotropic
smoothing.
-n value
The number of iterations. The higher the number of iterations,
the smoother the result.
-i list
A list of iterations at which output should be written to a file
(ranges such as 1-3,5,8 are allowed). If such a list is
entered, the -n option is ignored. By default, the entire vol-
ume will be written at each listed iteration, with the filename
outfile_file-nnn, where output_file is the name entered on the
command line, and nnn is the number of iterations, with leading
zeros as needed to give three digits. However, if the -o option
is entered, a single slice will be written at each of the speci-
fied iterations, all into the same output file.
-e ext An extension (excluding the dot) to put after the iteration num-
ber of the filename when writing files at selected iterations,
so the name has the form output_file-nnn.ext.
-o value
Single slice to output (numbered from 1). This option is useful
when adjusting parameters if you can judge the performance by
looking at just one slice. It will not make the program do the
computation on only one slice; it will still operate on the
whole input volume.
-m value
Mode for output file: 0 for byte, 1 for integer, 2 for real, or
6 for unsigned integer. By default, the output file will have
the same mode as the input file. This works for byte data
because densities will never become more extreme than in the
original volume. However, if you have byte input data with a
low dynamic range, you may need to specify real output to avoid
seeing discrete density levels in the smoothed regions.
-s value
Sigma value for smoothing or averaging the structure tensor,
which might give a more accurate estimate of the direction of an
edge. The default is 0 for no smoothing.
-t value
The time step. The product of the time step and the number of
iterations determines the amount of diffusion. The diffusion
will run faster with a higher time step but may become unstable.
-f Use faster but less accurate routine for computing eigenvectors.
With this option the program will run about 75% faster, but the
results will differ by about 1%. The difference is probably not
meaningful.
-P Print process ID to standard error.
EXAMPLES
To get a set of volumes, one at every third iteration, enter:
nad_eed_3d -i 3,6,9,12,15,18,21 -k 1.2 tomo.rec tomo.nad
This will produce tomo.nad-003, tomo.nad-006, etc. They can be visual-
ized with:
3dmod tomo.nad-*
To get a single file with one slice, say slice 16, from every iteration
from 5 to 15, enter:
nad_eed_3d -i 5-15 -k 1.2 -o 16 tomo.rec tomo.nad-1.2
To get a series of such files at different K values, just repeat the
above command, or (under tcsh) enter:
foreach i (0.6 0.8 1.0 1.2 1.4 1.6)
nad_eed_3d -i 5-15 -k $i -o 16 tomo.rec tomo.nad-$i
end
This will produce tomo.nad-0.6, tomo.nad-0.8, etc., which can be visu-
alized with:
3dmod tomo.nad-*.*
If your file is large (e.g., > 10 megavoxels), and you have determined
your optimal parameters, say 15 iterations with a K of 1.3, then pre-
pare a command file, e.g., nad.com, with the line:
$nad_eed_3d -k 1.3 -n 15 INPUTFILE OUTPUTFILE
(Do not indent the line; the $ must be the first character on the line.
Also, do not substitute your input and output files, the command file
really should say INPUTFILE and OUTPUTFILE.)
Then enter:
chunksetup -m 10 nad.com tomo.rec tomo.nad
If you are doing more than 8 iterations, you should increase the over-
lap between chunks by adding the option "-p #" where "#" is the number
of iterations; this will reduce the effects of cutting the volume into
chunks to a minor level. Overlap of 4 times the number of iterations
is needed to eliminate these effects but this could increase chunk
sizes substantially.
The Chunksetup command with option "-m 10" will produce command files
in which each run of the program will require less than 360 MB of mem-
ory (use a different amount to allow for more memory). On a single
processor machine, run these with:
subm nad-all
If multiple machines or processors are available, run in parallel with:
processchunks list_of_machines nad
or just
processchunks # nad
to run with # processors on the local machine.
FILES
If an output file already exists, it will be made a backup file by
adding ~ to its name.
AUTHORS
Achilleas Frangakis and Reiner Hegerl (IMOD modifications by David Mas-
tronarde). The program is copyright Max-Planck-Institut for Biochem-
istry, Martinsried, Germany.
SEE ALSO
chunksetup, processchunks, 3dmod
BUGS
Email bug reports to mast at colorado dot edu.
IMOD 4.11.0 nad_eed_3d(1)