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 this 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
image = image[:, :, 0]
Example 1 :
Python3
# importing various librariesimport mahotasimport mahotas.demosimport mahotas as mhimport numpy as npfrom pylab import imshow, show# loading nuclear imagenuclear = mahotas.demos.nuclear_image()# filtering imagenuclear = nuclear[:, :, 0]# adding gaussian filternuclear = mahotas.gaussian_filter(nuclear, 4)# setting thresholdthreshed = (nuclear > nuclear.mean())# creating distance mapdmap = mahotas.distance(threshed)print("Distance Map")# showing imageimshow(dmap)show()# numpy ones arrayBc = np.ones((3, 2))# getting maximamaxima = mahotas.morph.regmax(dmap, Bc = Bc)# showing imageprint("Maxima")imshow(maxima)show() |
Output :
Example 2 :
Python3
# importing required librariesimport numpy as npimport mahotasfrom pylab import imshow, show # loading imageimg = mahotas.imread('dog_image.png') # filtering the imageimg = img[:, :, 0] # setting gaussian filtergaussian = mahotas.gaussian_filter(img, 15) # setting threshold valuegaussian = (gaussian > gaussian.mean()) # creating a labelled imagelabelled, n_nucleus = mahotas.label(gaussian) # getting distance mapdmap = mahotas.distance(labelled)# showing imageprint("Distance Map")imshow(dmap)show()# numpy ones arrayBc = np.ones((4, 1))# getting maximamaxima = mahotas.morph.regmax(dmap, Bc = Bc)# showing imageprint("Maxima")imshow(maxima)show() |
Output :
