nad_eed_3d(1) General Commands Manual nad_eed_3d(1)NAMEnad_eed_3d - Nonlinear anisotropic diffusion, edge enhancing, in 3DSYNOPSISnad_eed_3d [options] input_file output_fileDESCRIPTIONnad_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-moption 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-kvalueThe 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.-nvalueThe number of iterations. The higher the number of iterations, the smoother the result.-ilistA 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-noption 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-ooption is entered, a single slice will be written at each of the speci- fied iterations, all into the same output file.-eextAn 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.-ovalueSingle 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.-mvalueMode 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.-svalueSigma 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.-tvalueThe 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.-fUse 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.-PPrint process ID to standard error.EXAMPLESTo 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.FILESIf an output file already exists, it will be made a backup file by adding ~ to its name.AUTHORSAchilleas Frangakis and Reiner Hegerl (IMOD modifications by David Mas- tronarde). The program is copyright Max-Planck-Institut for Biochem- istry, Martinsried, Germany.SEEALSOchunksetup, processchunks, 3dmodBUGSEmail bug reports to mast at colorado dot edu. IMOD 4.11.0 nad_eed_3d(1)