timjerman / jermanenhancementfilter Goto Github PK

Hi Tim,

I got a very desent result from your code. Most coronary artery has been captured. I tried the sigma value ranging from 0.25 to 16. The problem is there are lots of false positive especially heat mussel, bones and edge of the border. My understanding is the algorithm also captures the big object. Any thoughts how to remove those false positive region?
Here is one example from the results:
https://drive.google.com/open?id=1ZfSS6jMT70xitvITxXSVX1T9TKHa68vw

Best,
Jeffery

Hi,

I would like to first say thank you for the script for this filter, it made understanding the Frangi paper a lot easier. I only have a small question on for imgaussian() , is there any reason why you chose to filter each dimension of the image with their 1D gaussian instead of filtering the image with the 2D Gaussian?

PS: extra small question but it seems Kroon's Matlab script is wrong mathematically (at least for the 2D)?

Thank you,

Viet Than

Dear Tim,
Firstly, thanks for sharing the excellent work and code, it is very powerful and useful.

I’m trying to use it enhance liver vessels in CT volume. I provide an example (63.6MB) for better understanding and you can download it at your convenience.

From the enhancement results, I have two questions.
1. Why the default spacing setting [1, 1, 1] is better than the exact spacing in terms of visual evaluation of the enhancement results?

It can be seen the vessels are enhanced better in (c). However, intuitively, enhancement with the exact spacing should obtain better results. So I’m very puzzled about this situation.

**2. Why there are so many false positives in the liver borders and tumor borders?
And how to eliminate them without degenerate the true enhanced vessels?
**

As the yellow arrow points out, this region is obvious not vessel but it is enhanced.

Would it be possible for you to give me some of your insight about the two questions?

Best regards,
Jun Ma

Hi,

I found this repo is really useful to me. I am working on cardiac imaging. My input image is z512512 contrast CT scan. Do you have any suggestion about how to filter out coronary artery vessel? Any suggestion to the parameter setting?

Best,

Hello,

First of all, your method is awesome and already helped me a lot. I just have a question about the implementation.

In line 47 in vesselness3D.m:

you use min(Lambda3(:)).

However, in equation (13) in your journal paper, it seems to be max(Lambda3(:)).

Maybe, I misunderstood somewhere. Could you advice?

Thanks,
Jianxu

Hello,

Just want to first say what an amazing code this is and how useful it is for my field. I am trying to use it on micro-CT images of a mouse lung. Due to the nature of the vasculature in lungs, I am trying to preserve both very large vessels (~2mm in diameter) and very small (~15 microns in diameter). I have found a nice range of sigmas for the small to medium sized vessels (1:10). When I do this however, only parts of the outline of larger vessels are detected. When I increase the sigma range (1:40), I get a new problem of smaller vessels merging together.

Have you ever run into this during development? I think I understand why it is happening, but I am at a loss for how to fix it. Is it maybe just a limitation of the code that vessels that are so different in size cannot be characterized at the same time?

Any help you can provide would be greatly appreciated!

Cheers,

Eric