Workflows

imagemks.workflows.segment_fluor_cells(imgNuc, imgCyto, smooth_size, intensity_curve, short_th_radius, long_th_radius, min_frequency_to_remove, max_frequency_to_remove, max_size_of_small_objects_to_remove, peak_min_distance, size_after_watershed_to_remove, cyto_local_avg_size, zoomLev)

Segments fluorescent cells.

Parameters

  • imgNuc ((M,N) numpy array) – An image of nuclei with size (M,N)

  • imgCyto ((M,N) numpy array) – An image of the cytoskeleton with same size (M,N).

  • smooth_size (int, pixels) – The sigma of the gaussian.

  • intensity_curve (int) – Exponent of the curve used to fit intensities on range [0,1]

  • short_th_radius (int, pixels) – Radius of neighborhood used to calculate a local average threshold.

  • long_th_radius (int, pixels) – Radius of neighborhood used to calculate a local average threshold

  • min_frequency_to_remove (int, pixels) – Frequency in pixels used to define donut mask.

  • max_frequency_to_remove (int, pixels) – Frequency in pixels used to define donut mask.

  • max_size_of_small_objects_to_remove (float, micrometers^2) – Size beneath which no cells can exist.

  • peak_min_distance (int, pixels) – Min distance between nuclei.

  • size_after_watershed_to_remove (float, micrometers^2) – Size beneath which no cells can exist. Calculated after watershed.

  • cyto_local_avg_size (int, pixels) – Radius of neighborhood used to calculate a local average threshold

  • zoomLev (int) – Real magnification of the image.

Returns

(N, C) – N is a labeled nucleus image. Where each label corresponds to an individual cell. 0 corresponds to the background. C is a labeled cytockeleton image. The labels correspond to the closest nucleus in N.

Return type

list of (M,N) numpy arrays. Long dtype

imagemks.workflows.measure_fluor_cells(label_Nuc, label_Cyto, pix_size)

Generates measurements for labeled Nucleus images and labeled Cytoskeleton images.

Parameters

  • label_Nuc ((M,N) long dtype) – A labeled nucleus image. Where each label corresponds to an individual cell. 0 corresponds to the background.

  • label_Cyto ((M,N) long dtype) – A labeled cytockeleton image. The labels correspond to the closest nucleus in N. 0 corresponds to the background.

Returns

Measurements – Cell_Number, Nuc_Area_um2, Nuc_Perimeter_um, Nuc_Area_Factor, Nuc_Major_L_um, Nuc_Minor_L_um, Nuc_eccentricity, Nuc_orientation, Nucleus_eq_diameter_um, Cyto_Area_um2, Cyto_um, Cyto_Area_Factor, Cyto_orientation, Cyto_Major_L_um, Cyto_Minor_L_um

Return type

dataframe of measurements for each cell

imagemks.workflows.visualize_fluor_cells(L, A, thickness=1)

Colors the original image with the segmented image. Also marks borders of segmentation on the original image so that borders can be evaluated.

Parameters

  • L ((M,N) long dtype) – The labeled image that is a segmentation of A.

  • A ((M,N) or (M,N,3) array) – The original image. Grayscale and color are supported. thickness : Thickness of the borders in pixels. Default is 1. color : Tuple of 3 uint8 RGB values.

Returns

(v1, v2) – v1 is a colored original image. v2 is the original image with marked borders.

Return type

tuple of (M,N,3) arrays uint8 dtype

imagemks.workflows.default_parameters(cell_type)

Generates a dictionary of default paramaters.

Parameters

cell_type (string) – Either muscle or stem. More support coming soon.

Returns

params – Params defines smooth_size, intensity_curve, short_th_radius, long_th_radius, min_frequency_to_remove, max_frequency_to_remove, max_size_of_small_objects_to_remove, power_adjust, peak_min_distance, size_after_watershed_to_remove, and cyto_local_avg_size.

Return type

dictionary