image segmentation of carotid artery

I am trying to find the plaque in the carotid artery, and i want to make something which detects the edges of the wall of the artey but not any of the methods for edge tracking has helped. can you help me out?

the image is an ultra sound image.

this an image with plaque(represented by dotted lines)

this is a healthy artery

[darova]

Can you please attach the image?

[KALYAN ACHARJYA]

@Saurav Without observing the image, its not easy to answer related to segmenation.

[Hari Krishna Ravuri]

Hi,

I understand that you are trying to find the plaque by detection of edges in the wall of artery.As you have mentioned that none of the edge detection methods have helped you, please attach a sample image, so that a possible solution may be provided.

[SAURAV ANAND]

i have attached the images and sorry for the delay. And i am not supposed to use any image segmentation methods that uses predefined masking.

[Hari Krishna Ravuri]

Hi,

I understand that, you canot use segmentation, please try removing the noise and apply edge detection.The following references may help.

https://www.mathworks.com/help/images/ref/denoiseimage.html

https://www.mathworks.com/help/wavelet/ref/wdenoise2.html

[SAURAV ANAND]

i have the deep learnig toolbox installed but it still shows:

Undefined function or variable 'denoisingNetwork'.

i=imread('abnormal2.jpg')
g=rgb2gray(i);
net = denoisingNetwork('DnCNN');
noisyI = imnoise(i,'gaussian',0,0.01);
figure
imshowpair(i,noisyI,'montage');
title('Original Image (left) and Noisy Image (right)')
denoisedI = denoiseImage(noisyI, net);
figure
imshow(denoisedI)
title('Denoised Image')

but it shows the mentioned error at line 3

[darova]

How to inditificate a plaque and noise?

[SAURAV ANAND]

how did you get this output can you please share the code?

[darova]

I used this program

[SAURAV ANAND]

I found a research paper on this which shows to implement Completely User-Independent Layer EXtraction (CULEX) algorithm. But don't have the code. can anyone haelp me out with the code?

[SAURAV ANAND]

The exact algorithm consists of the following steps:

1) Low pass filtering of the image (gaussian filter of the 50th order, standard deviation equal to 10) in order to increase signal-to-noise ratio.

2) Determination of the adventitial wall from the intensity profile of the image considered column wise. Specifically, for each column of the image, we identify the pixels possibly belonging to the adventitia as those local maxima whose intensity is in the 90th percentile of the intensity distribution. An example of a typical intensity profile derived along a column of the image is reported in Fig. 2.

3) Individuation of the carotid lumen as the minimum point on the intensity profile whose mean intensity and variance of the neighborhood belong to the lowest classes. The minimum is searched descending the intensity profile from the maxima found during step 2). When the minimum is reached, the corresponding point is taken as marker of the carotid lumen and the starting maximum as marker of the adventitia.

4) Iteration of steps 2) and 3) for all columns.