<p>I looked at some picture from DICOM, and it seems that these images usually don't have many local minima, so I guess that's why watershed isn't optimal.
However, it seems that in DICOM the color gradients are often strong, so I suggest to use techniques that works well with gradients:</p>

<ul>
<li><p>Direct Gradient computations, either convolutional gradients or morphological gradients (selects shape of your different objects)</p></li>
<li><p>Normalized Cut on Similarity Graphs</p></li>
</ul>

<p>If you want to know more about these you can read <a href="https://ai.stackexchange.com/q/7617/2444">this post</a>.</p>

CC BY-SA 4.0
2018-10-04T07:49:48.753Z
2019-05-02T13:35:02.037Z
2019-05-02T13:35:02.037Z
16Aghnar
<p>As I'm beginner in image processing, I am having difficulty in segmenting all the parts in <a href="https://en.wikipedia.org/wiki/DICOM" rel="nofollow noreferrer">DICOM</a> image. </p>

<p>Currently, I'm applying <a href="https://en.wikipedia.org/wiki/Watershed_(image_processing)" rel="nofollow noreferrer"><em>watershed algorithm</em></a>, but it segments only that part that has tumour. </p>

<p>I have to segment all parts in the image. Which algorithm will be helpful to perform this task?</p>

<p>The image below contains the tumour.</p>

<p><a href="https://i.sstatic.net/3xtzl.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/3xtzl.png" alt="enter image description here"></a></p>

<p>This image is the actual DICOM image</p>

<p><a href="https://i.sstatic.net/zVgfu.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/zVgfu.png" alt="enter image description here"></a></p>

<computer-vision><matlab><image-segmentation>
How do I segment each part of a DICOM image?
Shehnaz Ameer
# How do I segment each part of a DICOM image?

(Asked by: username_0 on 2018-10-04)

As I'm beginner in image processing, I am having difficulty in segmenting all the parts in [DICOM](https://en.wikipedia.org/wiki/DICOM) image.

Currently, I'm applying [*watershed algorithm*](https://en.wikipedia.org/wiki/Watershed_(image_processing)), but it segments only that part that has tumour.

I have to segment all parts in the image. Which algorithm will be helpful to perform this task?

The image below contains the tumour.

[![enter image description here](https://i.sstatic.net/3xtzl.png)](https://i.sstatic.net/3xtzl.png)

This image is the actual DICOM image

[![enter image description here](https://i.sstatic.net/zVgfu.png)](https://i.sstatic.net/zVgfu.png)

**Tags:** computer-vision, matlab, image-segmentation


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## 1 answers

### Answer by username_1 on 2018-10-04. Score: 0

I looked at some picture from DICOM, and it seems that these images usually don't have many local minima, so I guess that's why watershed isn't optimal.
However, it seems that in DICOM the color gradients are often strong, so I suggest to use techniques that works well with gradients:

* Direct Gradient computations, either convolutional gradients or morphological gradients (selects shape of your different objects)
* Normalized Cut on Similarity Graphs

If you want to know more about these you can read [this post](https://ai.stackexchange.com/q/7617/2444).


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