QGIS Merging DEM's of Different Resolutions - merge

I wish a solution in QGIS to merge 2 DEM layers of different resolutions (20m & 250m) that overlap. I want to retain the extent of the 2m DEM with the 250m DEM being trimmed to the 2m extent. Is this possible please?

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Problem with creating a 3D mask of DICOM-RT contour data using MATLAB

I have troubles extracting a tumor using a RT mask from a dicom image. Due to GDPR I am not allowed to share the dicom images even though they are anonymized. However I am allowed to share the images themself. I want to extract the drawn tumor from the CT images using the draw GTV stored as a RT structure using MATLAB.
Lets say that the file directory where my CT images are stored is called DicomCT and that the RT struct dicom file is called rtStruct.dcm.
I can read and visualize my CT images as follows:
V = dicomreadVolume(“DicomCT”);
V = squeeze(V);
volshow(V)
volume V - 3D CT image
I can load my rt structure using:
Info = dicominfo(“rtStruct.dcm”);
rtContours = dicomContours(Info);
I get the plot giving the different contours.
plotContour(rtContours)
Contours for the GTV of the CT image
I used this link for the information on how to create the mask such that I can apply it to the 3D CT image: https://nl.mathworks.com/help/images/create-and-display-3-d-mask-of-dicom-rt-contour-data.html#d124e5762
The dicom information tells mee the image should be 3mm slices, hence I took 3x3x3 for the referenceInfo.
referenceInfo = imref3d(size(V),3,3,3);
rtMask = createMask(rtContours, 1, referenceInfo)
When I plot my rtMask, I get a grey screen without any trace of the mask. I think that something is wrong with the way that I define the referenceInfo, but I have no idea how to fix it or what is wrong.
volshow(rtMask)
Volume plot of the RT mask
What would be the best way forward?
i was actually having some sort of similar problem to you a couple of days ago. I think you might have two possible problems (none of them your fault).
Your grey screen might be an error rendering that it's not showing because of how the actual volshow() script works. I found it does some things i don't understand with graphics memory and representing numeric type volumes vs logic volumes. I found this the hard way in my job PC where i only have intel HD graphics. Using
iptsetpref('VolumeViewerUseHardware',true)
for logical volumes worked fine for me. You an also test this by trying to replot the mask as double instead of logical by
rtMask = double(rtMask)
volshow(rtMask)
If it's not a rendering error caused by the interactions between your system and volshow() it might be an actual confusion and how the createMask and the actual reference info it needs (created by an actual bad explanation in the tutorial you just linked). Using pixel size info instead of actual axes limits can create partial visualization in segmentation or even missing it bc of scale. This nice person explained more elegantly in this post by using actual geometrical info of the dicom contours as limits.
https://es.mathworks.com/support/search.html/answers/1630195-how-to-convert-dicom-rt-structure-to-binary-mask.html?fq%5B%5D=asset_type_name:answer&fq%5B%5D=category:images/basic-import-and-export&page=1
basically use
plotContour(rtContours);
ax = gca;
referenceInfo = imref3d(size(V),ax.XLim,ax.YLim,ax.ZLim);
rtMask = createMask(rtContours, 1, referenceInfo)
In addition to your code and it might work.
I hope this could be of help to you.

determining the properties of pores

I have several series of segmented images and I need to calculate the properties (area, perimeter, radius of the largest circle fitting in area) of the black areas (pores). I could not find the value with the software imagej as it seems that it has some problems in distinguishing the holes (569 area was found) and I tried to find the values by regionprops in matlab. however, it seems that it has the same problem (570 area was found). So, can anybody please help me find the solution to this question?
here is the areas found by imagej.
The black regions bleed into one another and ImageJ cannot distinguish them. If you use Process > Binary > Watershed, this will segregate the regions into (most likely) separate objects. Be aware that you may need to invert the image before doing this. Then you can use Analyze > Analyze Particles... to find the objects. The measurements that ImageJ produces can be controlled using Set Measurements and in the dialog for Analyze Particles. It will do area and perimeter for each object, but not (AFAIK) the radius of the largest circle.

Biomedical Image Segmentation

In brain tumor segmentation,can I consider Images and Labels as color images?
Or images can have 3 channels but Ground Truth/ Mask/ Label must be in 1 channel. Or both must be of 1 channel?? As I have used both (images & GT) of 3 channels for UNET architecture, and giving me output as blank colored image. Why output is so?
There is no necessary to use colored images to perform biomedical image segmentation. The value of CT/MR image has a specific meaning, which denotes different lesions such as bones or vessels.
If you use 3 channels, I don't know whether the value still has the same meaning or not. Also, I do not recommend you take the GT as 3 channels image, because the voxel value denotes different classes. In your case, maybe 1-n for different kinds of tumors, 0 for background.
Thus, 3 channels representation will lose some semantic information, make the problem more complex.

Differentiating size of Lego blocks in image

I wanted to ask how I could count certain type of Lego block in am image in MATLAB.
I am able to counts blocks of a certain color.
But I cannot seem to work out how to differentiate size and type of a certain block. I need to count the number of 4 by 2 blue blocks in a set of images.
I need count how many of this block
And this block are in the images below
This includes those that are upside down or at different orientations.
Examples of images are below.
In this image there are 3 blue and 1 red
In this image there is only 1 blue
Three blue and two red
Any help in MATLAB will be much appreciated.

Free satellite image for image segmentation testing

I need some free satellite images (panchromatic) to test some segmentation algorithms.
I have searched the web but I didn't find any resources our websites that provide free satellite images.
Thanks.
You can fill this form and request for a free samples from Geoeye of IKONOS imagery.
http://www.geoeye.com/corpsite/solutions/learn-more/sample-imagery.aspx
or alternatively GLCF has 4 IKONOS images samples that can be used. You can download them from here:
http://glcf.umd.edu/data/ikonos/
Note: IKONOS 2 has 4 multi-spectral bands of 4m resolution and 1 panchromatic band of 1m resolution. You can just use the Panchromatic band if that is your requirement.
General search engines of satellite granules
You can search and download Landsat images from Earthexplorer or Glovis services. You'll find several collections there.
Landsat panchromatic
Landsat ETM+ provide a panchromatic image at band 8 with 15m resolution. One example here, from WRS-2 Path 29 row 30.
LDCM misson
Be aware that Landsat LDCM mission scenes will be available soon at the same website, by the end of May.