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Mahotas – Getting Border of label at given region

Last Updated : 24 Feb, 2023
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In this article we will see how we can get the border of the label in the labelled image within the given region in mahotas. 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.labelled.border method 
 

Syntax : mahotas.labelled.border(labelled_image, i, j)
Argument : It takes numpy.ndarray object i.e labelled image and two integer as argument 
Note : A pixel is on the border if it has value i (or j)
Return : It returns numpy.ndarray object i.e labelled image with border label 
 

Note : The input of the this should be the filtered image object which is labelled 
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 
 

image = image[:, :, 0]

Example 1 : 
 

Python3




# importing required libraries
import mahotas
import numpy as np
from pylab import imshow, show
import os
 
# loading nuclear image
f = mahotas.demos.load('nuclear')
 
# setting filter to the image
f = f[:, :, 0]
 
# setting gaussian filter
f = mahotas.gaussian_filter(f, 4)
 
# setting threshold value
f = (f> f.mean())
 
# creating a labelled image
labelled, n_nucleus = mahotas.label(f)
 
 
# showing the labelled image
print("Labelled Image")
imshow(labelled)
show()
 
# getting border for label at given point
relabeled = mahotas.labelled.border(labelled, 0, 20)
 
# showing the image
print("Labels With borders at given point")
imshow(relabelled)
show()


Output : 
 

Example 2 : 
 

Python3




# importing required libraries
import numpy as np
import mahotas
from pylab import imshow, show
  
# loading image
img = mahotas.imread('dog_image.png')
    
# filtering the image
img = img[:, :, 0]
     
# setting gaussian filter
gaussian = mahotas.gaussian_filter(img, 15)
  
# setting threshold value
gaussian = (gaussian > gaussian.mean())
  
# creating a labelled image
labelled, n_nucleus = mahotas.label(gaussian)
   
print("Labelled Image")
# showing the gaussian filter
imshow(labelled)
show()
  
# getting border for label at given point
relabeled = mahotas.labelled.border(labelled, 1, 0)
 
# showing the image
print("Labels With borders at given point")
imshow(relabelled)
show()


Output : 
 

 



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