Problem with LeedTOR

[Amine Adjoud]

Hi, 

 I have a problem while using LeedsTOR: when I run the leeds.analyze() function, the regions of interest are not positioned in the right place. I tried with the parameter invert=true but I still have the same problem. Does anyone have a solution?

 Thanks in advance,

 Amine

[James Kerns]

This looks like a scaling issue. Is your phantom sitting on the EPID or at isocenter? 

The large noise and vertical banding could be affecting the ring detection. I would try applying a gaussian filter first to see if that fixes it. 

leeds = LeedsTOR(...)

leeds.image.filter(size=3, kind='gaussian')

leeds.analyze(...)

There is one other more involved option but let's see if that fixes it first. 

[Amine Adjoud]

I am using the phantom to evaluate the performances of a conventional radiology imaging. Is pylinac not compatible with this kind of tests?

The Gaussian filter is working but my ftm values are affecting by it size.

[James Kerns]

I don't know if others have used it for conventional radiology. In theory, as long as the phantom is at isocenter then it should work. If applying the gaussian filter results in a correct detection then the issue is indeed about the large noise in the image. There is a workaround, which is to override the size of the phantom:

# perform the gaussian filter like earlier to get a valid analysis

leeds = LeedsTOR(...)

leeds.image.filter(...)

leeds.analyze(...)

# now take the phantom center location value and pass it to a new analysis

size = leeds.phantom_radius

leeds2 = LeedsTOR(...)  # load the same image, but we don't filter this one

leeds2.analyze(..., size_override=size)

....

Let me know how it works out.

[Amine Adjoud]

Thanks! I have good results changing the size.

[Julio Almansa]

I'm not using it for conventional radiology but I tried for this use.

With the phantom on top of the detector and using raw images here is the analysis for two images (with or without Cu filter).

The code i used:

from pylinac import LeedsTOR
leeds = LeedsTOR('TOR18FG.dcm')
leeds.analyze(low_contrast_threshold=0.05, high_contrast_threshold=0.5)

I think that the only issue is with the High-frequency rMTF because the 9 ROIs used is not enough for the resolution of conventional radiology images.

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Julio Almansa López

Hosp. Universitario Virgen de las Nieves

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[James Kerns]

Julio, 

     Good to know, thanks! For my linac kV imaging 9 was more than enough 😁 I can work on including the other ROIs. 

[Julio Almansa]

James,

It would be fine if you can include more ROIs !

One question: Is there any way to change the estimator for the relative mtf to be the standard deviation of the ROI.

Thanks ?

JALmansa

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Julio Almansa López

Tfno Hospital: 647563335 (corp: 695836)

FEA Radiofisica Hospitalaria
UGC Física y Protección Radiológica

Hosp. Universitario Virgen de las Nieves

Avda. de las Fuerzas Armadas nº2. 18014, Granada
juliof.al...@juntadeandalucia.es

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jalmans...@gmail.com
Tlf: 659711957
skype: jalmansa_

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[James Kerns]

If you can find a paper or source that uses the standard deviation as the metric for calculating MTF then I will consider adding it. Up to now, I've not heard of doing such a thing.