How to create a histogram of a nifti file

In summary, when creating a histogram of a .nii file, it's important to consider the range of values and how they are being represented. In this conversation, the issue seems to be with setting all pixels within a certain range to 1, which may be causing the entire image to appear white. To fix this, it is suggested to adjust the range of values or use a different function to set the pixels. It is also important to make sure the file is being saved correctly and that the values are being saved as integers.
  • #1
sishan
1
0
Hi,
I'm trying to create a histogram of a .nii file but it's now working.
1. loading the nifti file:
>> Try2=load_nifti('DM.nii');
2. hist(Try2);
that generarates a histogram, where most of the values are concentrated between -150 and 200.(3 bars,the middle one is between -50 and 100).
3. I then use a function that sets all pixels in the range to 1 (white)
and all pixels that are out of range to 0 (black).
range=(inputFileName >= I_min & inputFileName <= i_max);
inputFileName(range)=1;
inputFileName(~range)=0;

4. Then I save the file and open it with ITKSnap
save_nifti(inputFileName,outputFileName,1);
but when I open it, it's almost all white.

Not sure what I'm doing wrong, please help.
Thanks in advance!
 
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  • #2


Hi there,

It seems like the issue may be in the way you are setting the pixels to 1 or 0. When creating a histogram, it's important to consider the range of values in the image and how they are being represented. It's possible that the majority of your image has values between -150 and 200, so when you set all pixels within that range to 1, it may be causing the entire image to appear white.

One suggestion would be to adjust the range of values you are setting to 1 or 0. Instead of using -150 and 200, try using a smaller range that encompasses the majority of your image values. You could also try using a different function to set the pixels, such as a thresholding function, to better isolate the values you want to represent in the histogram.

Additionally, make sure you are saving the file correctly and that the values are being saved as integers rather than floats. This could also affect how the image appears when opened in ITKSnap.

I hope this helps and good luck with your histogram! Let me know if you have any further questions or if this solution works for you.
 

1. How do I import a nifti file into a software for creating a histogram?

To create a histogram of a nifti file, you will first need to import the file into a suitable software such as MATLAB, Python, or Fiji. This can usually be done by using the "import" or "load" function and selecting the nifti file from your computer.

2. What is a nifti file and why is it commonly used for creating histograms?

A nifti file is a type of file format commonly used in neuroimaging to store and analyze brain images. It contains both the image data and the associated metadata. Nifti files are often used for creating histograms because they allow for easy manipulation and analysis of the image data.

3. Is it possible to create a histogram of a nifti file without any programming or coding knowledge?

Yes, there are various software programs and online tools available that allow for the creation of histograms from nifti files without any programming or coding knowledge. These tools often have a user-friendly interface and simple step-by-step instructions to follow.

4. Can I customize the bin size and range when creating a histogram of a nifti file?

Yes, most software programs and tools allow for customization of the bin size and range when creating a histogram from a nifti file. This can be helpful in visualizing the data in a more meaningful and informative way.

5. Are there any specific considerations to keep in mind when creating a histogram of a nifti file?

When creating a histogram of a nifti file, it is important to ensure that the data is properly pre-processed and that any outliers or artifacts are removed. It is also important to understand the data and choose an appropriate bin size and range for the histogram based on the range and distribution of the data.

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