Radiomics entropy=0?

radiomics
(Leandro) #1

Hi, a quick question.

No matter if I study a label after segmenting the largest cross section of the image or the tumor volume, I keep getting Entropy = -0.0 with Radiomics.

Any tip?
Thanks.
Leandro.

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Brain Gliomas, Texture Analysis and Machine Learning
(Joost Van Griethuysen) #2

@carba86 Is that the firstorder Entropy? If so, what are the values for firstorder:Range and the value for the setting “binWidth” you used during extraction?

An entropy of 0 usually points to a ‘flat region’, i.e. all voxels have the same gray value AFTER DISCRETIZATION, this can be caused in a situation where the range of grayvalues is (much) smaller than the binwidth, causing all voxels to belong to the same bin: i.e. same grayvalue and a ‘flat region’

Regards,

Joost

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(Leandro) #3

Thanks Joost and sorry it’s taken me a while to write you back. Analyzing numbers obtained with Radiomics, I see that this inconsistency does not only happen with Entropy but with other features as well, firstorder specially. I attach screen captures of Radiomics settings and numbers obtained (each column representing a different patient).

I look forward to hearing from you guys, you are always of great help.

Kind regards,
Leandro.

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(Joost Van Griethuysen) #4

The entropy 0 is indeed caused by a too-large bin width (set to 25 in your case). Many of your scans show a lot lower range (max ~4, range < 5). This will result in flat regions.

Moreover, some of your scans are VERY different (e.g. max ~15,000), which, as predicted, do not result in entropy = 0.

My advise would be to use a parameter file and enable normalization with an adapted bin width. See more on customizing the extraction and the parameter file in pyradiomics’ documentation

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(Leandro) #5

Thanks Joost once again.
Do you think binwidth setting will correct other discrepancies I see for example in ngtdm or glcm ?

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