In this article we will see how we can highlight the maxima of image in mahotas. Maxima can be best found in the distance map image because in labeled image each label is maxima but in distance map maxima can be identified easily. For this we are going to use the fluorescent microscopy image from a nuclear segmentation benchmark. We can get the image with the help of command given below
mahotas.demos.nuclear_image()
Below is the nuclear_image
In order to do this we will use mahotas.morph.regmax
method
Syntax : mahotas.morph.regmax(img, Bc)
Argument : It takes image object and numpy ones array as argument
Return : It returns image object
Note : The input of the this should should be the filtered image or loaded as grey
In order to filter the image we will take the image object which is numpy.ndarray and filter it with the help of indexing, below is the command to do this
iamge = image[:, :, 0]
Example 1 :
# importing various libraries import mahotas import mahotas.demos import mahotas as mh import numpy as np from pylab import imshow, show # loading nuclear image nuclear = mahotas.demos.nuclear_image() # filtering iamge nuclear = nuclear[:, :, 0 ] # adding gaussian filter nuclear = mahotas.gaussian_filter(nuclear, 4 ) # setting threshold threshed = (nuclear > nuclear.mean()) # creating distance map dmap = mahotas.distance(threshed) print ( "Distance Map" ) # showing image imshow(dmap) show() # numpy ones array Bc = np.ones(( 3 , 2 )) # getting maxima maxima = mahotas.morph.regmax(dmap, Bc = Bc) # showing image print ( "Maxima" ) imshow(maxima) show() |
Output :
Example 2 :
# importing required libraries import numpy as np import mahotas from pylab import imshow, show # loading iamge img = mahotas.imread( 'dog_image.png' ) # filtering the imagwe img = img[:, :, 0 ] # setting gaussian filter gaussian = mahotas.gaussian_filter(img, 15 ) # setting threshold value gaussian = (gaussian > gaussian.mean()) # creating a labeled image labeled, n_nucleus = mahotas.label(gaussian) # getting distance map dmap = mahotas.distance(labeled) # showing image print ( "Distance Map" ) imshow(dmap) show() # numpy ones array Bc = np.ones(( 4 , 1 )) # getting maxima maxima = mahotas.morph.regmax(dmap, Bc = Bc) # showing image print ( "Maxima" ) imshow(maxima) show() |
Output :
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