imodfindbeads(1) imodfindbeads(1)NAMEimodfindbeads - Find gold particles in imagesSYNOPSISimodfindbeads options input_image output_modelDESCRIPTIONImodfindbeads 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-storeoption, 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:-sizeto specify the bead size,-areato specify a model with contours around areas to ana- lyze,-lightif beads are light on a dark background,-storeto control storage of peaks in the model as just described,-spacingto allow points closer together than the bead size,-sectionsto select the sec- tions to be analyzed, and-maxsecto 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-linearand add some filtering with either-kernelor-rad2and-sig2.There are many other options that were added during program development and can be ignored.OPTIONSImodfindbeads 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 -). Options can be abbreviated to unique letters; the currently valid abbreviations for short names are shown in parentheses.-input(-inp)OR-InputImageFileFilenameName of input image file. If it is not entered with this option it must be entered with the first non-option argument.-output(-o)OR-OutputModelFileFilenameName of output model file. If it is not entered with this option it must be entered with the second non-option argument.-filtered(-fi)OR-FilteredImageFileFilenameOutput 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(-ar)OR-AreaModelFilenameModel with contours enclosing areas to analyze or to exclude from analysis, depending on whether the -exclude option is given also. More than one contour can be included on each section. If there are no contours on a section within the range being analyzed, the contours on the nearest section with contours will be used.-exclude(-e)OR-ExcludeInsideAreasUse the contours in the area model to define regions to exclude from analysis rather than regions to include.-query(-q)OR-QueryAreaOnSectionIntegerReport area in megapixels that an area model includes in the analysis for the given section, and then exit. This is the sum of areas inside the contours, or the whole image area minus that sum if -exclude is given. With this option, only the input and area models need to be entered.-prexf(-pr)OR-PrealignTransformFileFilenameFile with transformations applied to align the images being ana- lyzed. The program will assume that the transformations consist only of shifts and will use this information to avoid finding beads at the edge of a filled area that has no image data.-imagebinned(-im)OR-ImagesAreBinnedIntegerThe current binning of the images relative to the original data. This factor is needed to scale prealignment transforms. The default is 1.-addOR-AddToModelFilenameModel 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.-refOR-ReferenceModelFilenameModel with all beads marked in defined areas, used for determin- ing the accuracy of the bead detection.-boundary(-bou)OR-BoundaryObjectIntegerObject in reference model with contours around the areas where beads have been fully marked.-size(-siz)OR-BeadSizeFloatingpointSize 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(-lig)OR-LightBeadsBeads are light on dark background-scaled(-sc)OR-ScaledSizeFloatingpointSize 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.-adjust(-adj)OR-AdjustSizesChange all size-based parameters using the measured size of the averaged bead. After averaging selected beads, the program will estimate the bead diameter by forming a radial average, finding the radius where the density falls off the fastest, fitting a line to nearby points with sufficiently high gradient, and find- ing the intersection of that line with the background density at the edge of the average. If the change is more than 5%, the program will add a third pass through the data. If the change is more than a factor of 1.6, the change in size will be rejected as implausible. This method does not give the right diameter for gold on plastic sections, so this option should be used only for cryo-samples or other samples taken with signifi- cant underfocus.-interpmin(-int)OR-MinInterpolationFactorFloatingpointWhen 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(-lin)OR-LinearInterpolationIntegerThis option controls the type of interpolation used in scaling images. Enter 1 to use linear instead of cubic interpolation; this option will help to reduce noise. Alternatively, enter -1 to use antialiased image reduction when images are being scaled down. With this option, large size reductions will be done in one step instead of with binning then interpolation. The noise reduction from antialias filtering would probably make kernel filtering unnecessary.-center(-c)OR-CenterWeightFloatingpointThe weighting for the center pixel in the edge detecting filter; 1 and 2 correspond to Prewitt and Sobel filters, respectively; the default is 2.-boxOR-BoxSizeScaledIntegerBox size for correlating and averaging beads in scaled down images. The default is 3 times the scaled size plus 2.-threshold(-t)OR-ThresholdForAveragingFloatingpointThreshold 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(-st)OR-StorageThresholdFloatingpointThreshold 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.)-fallback(-fa)OR-FallbackThresholdsTwointegersNumber of peaks to average to make the reference for the second round, and number of peaks to store in the model, if no dip is found when analyzing the histogram of the respective set of peaks. If this option is not entered, or if 0 is entered for one of the fallbacks, then the program exits with an error after failing to find a histogram dip.-bkgd(-bk)OR-BackgroundGroupsFloatingpointAfter 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(-an)OR-AnnulusPercentileFloatingpointBy 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(-pe)OR-MinRelativeStrengthFloatingpointMinimum 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(-sp)OR-MinSpacingFloatingpointMinimum 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(-se)OR-SectionsToDoListofintegerrangesList of sections to run. Comma-separated ranges can be entered; sections are numbered from 0. By default, all sections will be analyzed.-maxsec(-ma)OR-MaxSectionsPerAnalysisIntegerMaximum 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(-rem)OR-RemakeModelBeadStart 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(-g)OR-MinGuessNumBeadsIntegerA 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(-me)OR-MeasureToUseIntegerMeasure 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(-k)OR-KernelSigmaFloatingpointSigma 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.-rad1OR-FilterRadius1FloatingpointLow 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.-rad2OR-FilterRadius2FloatingpointHigh 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.-sig1OR-FilterSigma1FloatingpointSigma 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.-sig2OR-FilterSigma2FloatingpointSigma value for the Gaussian rolloff below and above the cutoff frequencies specified by FilterRadius1 and FilterRadius2-verbose(-v)OR-VerboseKeysTextstringKey letters for verbose output (1 for general, p for peak, f for first, l for last, e for every hist)-dump(-d)OR-DumpHistogramFileFilenameName of file in which to write all histograms. Each histogram will be written with a type number, the peak strength, and the actual or smoothed number of counts. The program will use suc- cessive type numbers and print a line describing the histogram written with each type number. Histograms can be displayed with commands like onegenplot -sym 0 -ty <type> <filename> where <type> is a type number and <filename> is the name pro- vided with this option. Use "-sym 0,0" and -ty "type1,type2" to show two curves, etc. Add the option "-ylog 1,10" to spread out the low parts of the histogram.-param(-pa)OR-ParameterFileParameterfileRead parameter entries as keyword-value pairs from a parameter file.-help(-h)OR-usagePrint help output-StandardInputRead parameter entries from standard inputAUTHORDavid MastronardeSEEALSObeadtrackBUGSEmail bug reports to mast at colorado dot edu. IMOD 4.9.5 imodfindbeads(1)