Mahotas – Highlighting Image Maxima

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 :

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# 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()

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Output :

Example 2 :

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# 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()

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Output :

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