How to do image segmentation using deep belief network

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.

[Image Analyst]

What deep learning toolbox? It's not in the product list below. Is it some third party toolbox? If so, what is the link to it?

[Aik Hong]

This one i mean: http://github.com/rasmusbergpalm/DeepLearnToolbox

[Image Analyst]

Probably no one here has used their toolbox, so you're best off contacting the authors.

[Aik Hong]

Thanks, I guess so too. But anyway i got to try to ask around to get as many info as i can. Hopefully the owner will be able to answer me then.