imodfindbeads(1) imodfindbeads(1) NAME imodfindbeads - Find gold particles in images SYNOPSIS imodfindbeads options in_image out_model DESCRIPTION Imodfindbeads finds gold particles or other circular densities (beads) in images by a combination of cross-correlation and other methods. It starts by correlating with a model of a spherical bead of a specified size, then forms an average out of the most strongly-correlating subset and repeats the procedure by correlating with the average. It analyzes the distribution of correlation strengths to find the strength that best separates the particles of interest from similar densities. The positions of the beads are stored in an IMOD model along with strengths for each. The points can then be visualized in 3dmod, and with the help of the Bead Fixer module, the threshold can be adjusted and points below threshold can be deleted. Rather than cross-correlating with a model or averaged bead, the pro- gram applies an edge-detecting filter (Sobel, by default) to both the images and the reference, and correlates the filtered images. This method improves the detectability of the beads and may improve the accuracy of the center positions. However, it only works well for beads in a certain size range, so the program first scales the images to bring the beads to a specified size (8, by default). The peaks in this correlation are the set of candidate positions for the beads. At each position, the program then computes an integral of the bead density relative to the background in an annulus around the bead. The program can then work with three measures of peak strength. One is the strength of the Sobel-filter correlation (which includes a component based on the density of the bead, a factor lost when using a normalized correlation coefficient). The second is the integrated density, and the third is the geometric mean of the first two. Whichever measure is chosen, it is scaled so that the maximum value is 1. Correlation with a simple item like a bead always produces many more peaks than actual beads, but a histogram of peak strength generally shows a dip between actual beads and spurious peaks. The program thus computes a histogram and smooths it with kernel smoothing, whereby a narrow distribution function instead of a single point is added into the histogram at every peak position. The width of this function is the kernel width, referred to as H in program output. The program tries a series of widths, from 0.2 downward, until it finds a dip in the histogram; then it computes it again with a kernel width of 0.05 in order to locate the dip more accurately. After the initial correlation with a model bead, the program uses the histogram analysis to select beads to average as a template for the second round correlation. If the analysis fails, it is possible to bypass it by entering a relative peak strength to use as a criterion for selecting beads. After the second round of correlations, the loca- tion of the dip is used to determine which points to output in the model. The default is to output a number of points below the dip so that the user can check and adjust the threshold if necessary. How- ever, with the -store option, you can output just the points above the dip or a certain fraction of the strongest peaks above the dip. Or, if the histogram analysis fails, this option can be used to bypass it and specify the actual peak strength to use as the criterion for output. The most significant options described below are: -size to specify the bead size, -area to specify a model with contours around areas to ana- lyze, -light if beads are light on a dark background, -store to control storage of peaks in the model as just described, -spacing to allow points closer together than the bead size, -sections to select the sec- tions to be analyzed, and -maxsec to set how many of them will be ana- lyzed in one group. In addition, if images are noisy, it may be help- ful to use linear interpolation with -linear and add some filtering with either -kernel or -rad2 and -sig2. There are many other options that were added during program development and can be ignored. Options Imodfindbeads uses the PIP package for input (see the manual page for pip). Options can be specified either as command line arguments (with the -) or one per line in a command file (without the -): -input OR -InputImageFile File name Name of input image file. If it is not entered with this option it must be entered with the first non-option argument. -output OR -OutputModelFile File name Name of output model file. If it is not entered with this option it must be entered with the second non-option argument. -filtered OR -FilteredImageFile File name Output file for images after they have been scaled and Sobel filtered. The coordinate system in the header will be congruent with that of the original image file so that the model can be displayed on it. -area OR -AreaModel File name Model with contours enclosing areas to analyze. More than one contour can be included on each section. If there are no con- tours on a section within the range being analyzed, the entire section will be used. -add OR -AddToModel File name Model to append to. After the analysis of histograms and thresholds, detected points will be eliminated if they are within the criterion spacing of a point in an existing object (where closed contour objects are excluded). Points will be stored in new objects. -ref OR -ReferenceModel File name Model with all beads marked in defined areas, used for determin- ing the accuracy of the bead detection. -boundary OR -BoundaryObject Integer Object in reference model with contours around the areas where beads have been fully marked. -size OR -BeadSize Floating point Size of beads in pixels, a required entry. A model bead of this size is constructed for the first round of correlation, and this size together with the scaled size determine how much images will be scaled for filtering. -light OR -LightBeads Beads are light on dark background -scaled OR -ScaledSize Floating point Size of beads in images scaled down for filtering; this entry together with the bead size determine the amount of scaling. In tests, values of 7 to 10 have been found to give the best detec- tion with Sobel filter. The default value is 8. -interpmin OR -MinInterpolationFactor Floating point When images are being scaled down, this entry determines how much of the scaling down must be done with interpolation instead of binning. Interpolation will preserve high frequency informa- tion better than binning does but may amplify noise. The default value is 1.4, which means that data will not be binned unless they are being scaled down by a factor of at least 2.8. This entry makes no difference unless images are being scaled down by more than a factor of 2. -linear OR -LinearInterpolation Use linear instead of cubic interpolation; this option will help to reduce noise. -center OR -CenterWeight Floating point The weighting for the center pixel in the edge detecting filter; 1 and 2 correspond to Prewitt and Sobel filters, respectively; the default is 2. -box OR -BoxSizeScaled Integer Box size for correlating and averaging beads in scaled down images. The default is 3 times the scaled size plus 2. -threshold OR -ThresholdForAveraging Floating point Threshold relative peak strength or number of beads for averag- ing. With a non-zero entry, selected beads from the first round of filtering and correlation are averaged to produce a reference for a second round. If a negative value is entered, the program will analyze the histogram of peak strengths and find the dip indicating the best boundary between actual and false beads. The value has 4 different meanings depending on the range: Greater than 1: an absolute number of beads with the strongest peaks Between 0 and 1: minimum relative peak strength Between 0 and -1: negative of strongest fraction of peaks above histogram dip -2: 1/4 of way from histogram dip to histogram peak (the default) -store OR -StorageThreshold Floating point Threshold relative peak strength for storing peaks in model. With a value of 0 (the default), the program will find the dip in the histogram of peak strengths, find the mean and SD of the strengths above the dip, and store all of the beads above the dip plus additional ones below the dip. The latter will be up to the 5 SD's below the mean or up to the number of ones above the dip. Enter a number between 0 and 1 to specify a relative strength above which peaks will be stored. Enter a negative number to specify the number to store as a fraction of the num- ber above the histogram dip (e.g., -1 for all points above the dip, -0.33 for the strongest 1/3 above the dip, -1.33 for all above plus 1/3 that many below the dip.) -bkgd OR -BackgroundGroups Floating point After finding peaks, the program will sort the peaks based on the background density into the number of groups given by this entry, as long as there are at least 100 peaks in each group. The histogram will be analyzed separately for each group to find the dip, and then the peak strengths will be scaled so as to superimpose the dip values. This scaling should make a single threshold value work better across a range of intensities. The default value is 4; enter 0 to prevent this analysis. -annulus OR -AnnulusPercentile Floating point By default, the program will use the mean in an annulus around the bead as the background for the analysis by groups. This entry specifies a percentile of the pixel values to use instead (e.g., 0.5 for the median). -peakmin OR -MinRelativeStrength Floating point Minimum relative peak strength, after any background scaling, for keeping a peak in the analysis. Too many weak peaks can prevent a dip from showing up in the smoothed histogram of strengths. The default is 0.1, or 0.05 if a threshold for aver- aging is being found from histograms. -spacing OR -MinSpacing Floating point Minimum spacing between peaks as a fraction of the bead size. When two peaks are closer than this distance apart, the weaker one is eliminated. The default is 1, but values of 0.8 to 0.9 are helpful for getting a more complete set of beads. -sections OR -SectionsToDo List of integer ranges List of sections to run. Comma-separated ranges can be entered; sections are numbered from 0. By default, all sections will be analyzed. -maxsec OR -MaxSectionsPerAnalysis Integer Maximum number of sections to include in one analysis. With this entry, the list of sections will be divided into groups no bigger than this size. Each group will be analyzed separately and results will be stored in a separate model object with its own threshold value. By default, all sections are analyzed together. -remake OR -RemakeModelBead Start with a model bead for each separate analysis when more than one group of sections is being analyzed. The default is to use the average from the previous group for the first round of correlation on a group. -guess OR -MinGuessNumBeads Integer A guess for the minimum number of beads per section. This entry may sometimes be required to help the program find a dip in the histogram, especially if there are very few beads. -measure OR -MeasureToUse Integer Measure to use for peak strengths: 0 for the correlation peak, 1 for the integral of density above the background, 2 for the geo- metric mean of these two. The default is 1; integrals were slightly better in test data sets. -kernel OR -KernelSigma Floating point Sigma for real-space smoothing with a Gaussian kernel (in pix- els). The smoothing is with a 3x3, 5x5 or 7x7 kernel whose coefficients are proportional to a Gaussian with the given sigma centered on the central pixel. This smoothing is applied before the image is scaled for filtering. The default is 0.85, which is equivalent to the simple smoothing filter in Clip and 3dmod. -rad1 OR -FilterRadius1 Floating point Low spatial frequencies in the cross-correlation will be attenu- ated by a Gaussian curve that is 1 at this cutoff radius and falls off below this radius with a standard deviation specified by FilterSigma2. Spatial frequency units range from 0 to 0.5. Use FilterSigma1 instead of this entry for more predictable attenuation of low frequencies. -rad2 OR -FilterRadius2 Floating point High spatial frequencies in the cross-correlation will be atten- uated by a Gaussian curve that is 1 at this cutoff radius and falls off above this radius with a standard deviation specified by FilterSigma2. -sig1 OR -FilterSigma1 Floating point Sigma value to filter low frequencies in the correlations with a curve that is an inverted Gaussian. This filter is 0 at 0 fre- quency and decays up to 1 with the given sigma value. However, if a negative value of radius1 is entered, this filter will be zero from 0 to |radius1| then decay up to 1. -sig2 OR -FilterSigma2 Floating point Sigma value for the Gaussian rolloff below and above the cutoff frequencies specified by FilterRadius1 and FilterRadius2 -verbose OR -VerboseKeys Text string Key letters for verbose output (1 for general, p for peak, f for first, l for last, e for every hist) -param OR -ParameterFile Parameter file Read parameter entries as keyword-value pairs from a parameter file. -StandardInput Read parameter entries from standard input AUTHOR David Mastronarde SEE ALSO beadtrack BUGS Email bug reports to mast at colorado dot edu. BL3DEMC 4.3.7 imodfindbeads(1)