How to do image segmentation using deep belief network
6 views (last 30 days)
Show older comments
Hi all, I’m currently doing a project on image segmentation. I have a few datasets of CT scan slices image of a few patients. One dataset consists of around 170 slices of CT scan image.
I’ve manually segmented the region of interest using Matlab imfreehand tool. Thus I have one set of the original image together with another set of segmented image (in binary form).
Original images: 512x512 uint16 (IM-0001-0001.dcm till IM-0001-0170.dcm)
Manually segmented images: 512x512 logical (AAAmanual1.mat till AAAmanual170.mat)
I’ve downloaded the deep belief network Matlab source codes in the deep learning toolbox. As I know, we have to setup and train the DBN, then we can use the trained DBN to automatically segment the image and get the output as the segmented region.
But I have no idea how should I proceed from here to setup and train the DBN, then use it to segment the region that I want, given the input image (or original image whichever more suitable)? What else parameters do I need to change/adjust? How should I write the matlab code for this?
Need your help to suggest / advice how can I proceed from here… your help is very much appreciated. Thank you.
4 Comments
Image Analyst
on 4 Feb 2015
Probably no one here has used their toolbox, so you're best off contacting the authors.
Answers (0)
See Also
Categories
Find more on Image Data Workflows in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!