auto_crop_fast {synapsis} | R Documentation

## auto_crop_fast

### Description

crop an image around each viable cell candidate.

### Usage

    auto_crop_fast(
      img_path,
      max_cell_area = 20000,
      min_cell_area = 7000,
      mean_pix = 0.08,
      annotation = "off",
      blob_factor = 15,
      bg_blob_factor = 10,
      offset = 0.2,
      final_blob_amp = 10,
      test_amount = 0,
      brush_size_blob = 51,
      sigma_blob = 15,
      channel3_string = "DAPI",
      channel2_string = "SYCP3",
      channel1_string = "MLH3",
      file_ext = "jpeg",
      third_channel = "off",
      cell_aspect_ratio = 2,
      strand_amp = 2,
      path_out = img_path,
      resize_l = 720,
      crowded_cells = "FALSE",
      watershed_radius = 50,
      watershed_tol = 0.2,
      cropping_factor = 1.3
    )

### Arguments

`img_path,` | path containing image data to analyse
`max_cell_area,` | Maximum pixel area of a cell candidate
`min_cell_area,` | Minimum pixel area of a cell candidate
`mean_pix,` | Mean pixel intensity of cell crop (in SYCP3 channel) for normalisation
`annotation,` | Choice to output pipeline choices (recommended to knit)
`blob_factor,` | Contrast factor to multiply original image by before smoothing/smudging
`bg_blob_factor,` | Contrast factor to multiply original image by to take background. Used prior to thresholding.
`offset,` | Pixel value offset from bg_blob_factor. Used in thresholding to make blob mask.
`final_blob_amp,` | Contrast factor to multiply smoothed/smudged image. Used in thresholding to make blob mask.
`test_amount,` | Optional number of first N images you want to run function on. For troubleshooting/testing/variable calibration purposes.
`brush_size_blob,` | Brush size for smudging the synaptonemal complex channel to make blobs
`sigma_blob,` | Sigma in Gaussian brush for smudging the synaptonemal complex channel to make blobs
`channel3_string` | Optional. String appended to the files showing the channel illuminating cell structures. Defaults to DAPI, if third channel == "on".
`channel2_string` | String appended to the files showing the channel illuminating synaptonemal complexes. Defaults to SYCP3
`channel1_string` | String appended to the files showing the channel illuminating foci. Defaults to MLH3
`file_ext` | file extension of your images e.g. tif jpeg or png.
`third_channel` | Optional, defaults to "off". Set to "on" if you would also like crops of the third channel.
`cell_aspect_ratio` | Maximum aspect ratio of blob to be defined as a cell
`strand_amp` | multiplication of strand channel for get_blobs function.
`path_out,` | user specified output path. Defaults to img_path
`resize_l` | length for resized image
`crowded_cells` | TRUE or FALSE, defaults to FALSE. Set to TRUE if you have many cells in a frame that almost touch
`watershed_radius` | Radius (ext variable) in watershed method used in strand channel. Defaults to 1 (small)
`watershed_tol` | Intensity tolerance for watershed method. Defaults to 0.05.
`cropping_factor` | size of cropping window square, as factor of characteristic blob radius. Defaults to 1. May need to increase if using watershed.

### Details

This function takes all images in a directory, and crops around individual cells according to the antibody that stains synaptonemal complexes e.g. SYCP3. First, it increases the brightness and smudges the image with a Gaussian brush, and creates a mask using thresholding (get_blobs). Then it deletes cell candidates in the mask deemed too large, too small, or too long (keep_cells). Using the computeFeatures functions from EBImage to locate centre and radius, the cropping area is determined and the original image cropped. These images are saved in either a user specified directory, or a crops folder at the location of the image files.

### Value

cropped synaptonemal complex and foci channels around single cells, regardless of stage

### Author(s)

Lucy McNeill

### Examples

    demo_path = paste0(system.file("extdata",package = "synapsis"))
    auto_crop_fast(demo_path, annotation = "on", max_cell_area = 30000,
    min_cell_area = 7000, file_ext = "tif",crowded_cells = TRUE)

[Package synapsis version 1.0.0 Index]