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Segmentation of a foot MRI scan

Entry posted by mikefazz · - 521 views

So I have seen some questions here on embodi3D asking how to work with MRI data.  I believe the main issue to be with attempting to segment the data using a threshold method.  The democratiz3D feature of the website simplifies the segmentation process but as far as I can tell relies on thresholding which can work somewhat well for CT scans but for MRI is almost certain to fail.  Using 3DSlicer I show the advantage of using a region growing method (FastGrowCut) vs threshold.

 

The scan I am using is of a middle aged woman's foot available here

MRI_Data.png

 

The scan was optimized for segmenting bone and was performed on a 1.5T scanner.  While a patient doesn't really have control of scan settings if you are a physician or researcher who does; picking the right settings is critical.  Some of these different settings can be found on one of Dr. Mike's blog entries.

 

For comparison purposes I first showed the kind of results achievable when segmenting an MRI using thresholds.

MRI_Segmentation_Thresh.png

 

With the goal of separating the bones out the result is obviously pretty worthless.  To get the bones out of that resultant clump would take a ridiculous amount of effort in blender or similar software:

BetterWay.jpg

 

If you read a previous blog entry of mine on using a region growing method I really don't like using thresholding for segmenting anatomy.  So once again using a region growing method (FastGrowCut in this case) allows decent results even from an MRI scan.

 

MRI_Seg-RG.png

 

Now this was a relatively quick and rough segmentation of just the hindfoot but already it is much closer to having bones that could be printed.  A further step of label map smoothing can further improve the rough results.

MRI-Seg_RG-SM_Calc.png

 

The above shows just the calcaneous volume smoothed with its associated surface generated.  Now I had done a more proper segmentation of this foot in the past where I spent more time to get the below result

Slcr_3DVolume.jpg

 

If the volume above is smoothed (in my case I used some of my matlab code) I can get the below result.

MRI_Seg_Smooth.jpg

 

Which looks much better.  Segmenting a CT scan will still give better results for bone as the cortical bone doesn't show up well in MRI's (why the metatarsals and phalanges get a bit skinny), but CT scans are not always an option.

 

So if you have been trying to segment an MRI scan and only get a messy clump I would encourage you to try a method a bit more modern than thresholding.  However, keep in mind there are limits to what can be done with bad data.  If the image is really noisy, has large voxels, or is optimized for the wrong type of anatomy there may be no way to get the results you want.


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Thresholding is also my least favorite method of segmenting. I work in a radiation oncology department with access to some fantastic contouring software (MIM, Raystation, Eclipse, Pinnacle). Unfortunately, none of them have simple volume export functions. We've written a simple script which takes a Dicom structure file and outputs a simple CSV file with the contour point cloud. Using these tools along with 3DSlicer we generate volumes from these contours that seem to be much more accurate, have less noise, and are produced much faster than with the tools in 3DSlicer. Hopefully the contouring tools found in those softwares will make their way to 3DSlicer someday.

Screen Shot 2017-04-17 at 11.32.23 AM.png

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