http://imagej.273.s1.nabble.com/Calculate-the-concentration-in-a-CT-image-tp5022621p5022627.html
> Hi Kenneth and Stein,
>
> Thank you for your kind replies.
>
> To summarize the problem in one sentence, it is to replace the CT number
> with concentration value or whatever else we want.
> I believe interpolation can work. Could you please give me some hints for
> interpolation implement in ImageJ (or to replace CT number with
> concentration.)?
>
> Thank you so much.
> Yongqiang
>
> -----Original Message-----
> From: Stein Rørvik <
[hidden email]>
> Sent: 08 November 2019 01:54
> To:
[hidden email]
> Subject: Re: Calculate the concentration in a CT image
>
> Yes this is doable as per Kenneth's explanation, but you really need to
> understand the physics involved in your imaging.
>
> If you are using monochromatic X-rays (from a synchrotron) and your
> software's "CT number" is proportional to your material's linear
> attenuation coefficient, then the simple linear interpolation "method a"
> will work. As this is quite unlikely (you probably have a polychromatic
> source if you are using an in-house CT system), it greatly depends on
> whether or not your elements distribution is radially symmetric in all
> directions. The reason for this is that the X-rays loose energy as they
> pass through the sample, so the apparent concentration in the central parts
> will be lower than in the outer parts. This phenomenon is called "beam
> hardening". You can compensate this with X-Ray filtering, or software
> corrections (if the distribution is symmetric). My experience is that
> software corrections work better, as filtering really kills the signal
> noise ratio. Anyway your CT software must still be calculating the
> attenuation coefficients correctly, and that greatly depends on how clever
> your software is.
>
> This is in any case easy to check: Just scan a round plastic container
> with pure KI brine, and then check the radial profile. Is it flat? If yes,
> then "method b" should work; it probably needs an exponential profile. If
> it is not flat, you must revise your imaging setup and/or your CT software
> processing settings. If the KI profile is flat, repeat the experiment with
> pure water. If that is flat too, even "method a" should work. If KI is your
> heaviest compound in your system and the overall concentration is low, and
> all your other elements are light (low atomic numbers), then "method a"
> might also work even if the test profiles for KI is not flat. But again
> that will depend on your elements' distribution in the sample and the
> symmetry of everything. So again you need to understand the X-Ray imaging
> physics and how it applies to your sample.
>
> It will help if you post some example images, including all instrument
> related metadata. Also please tell what instrument and what software you
> are using for the generation of the CT images. I have considerable
> experience with such measurements from µCT images so I should be able to
> see if your images are analyzable or not.
>
> Stein
>
> -----Original Message-----
> From: ImageJ Interest Group <
[hidden email]> On Behalf Of Kenneth
> Sloan
> Sent: 7. november 2019 21:35
> To:
[hidden email]
> Subject: Re: Calculate the concentration in a CT image
>
> Knowing nothing about this particular application, I will assume nothing.
>
> So far, you seem to have two pairs of (CT Number, concentration):
>
> (loCT, loConcentration)
> (hiCT, hiConcentration)
>
> You want to convert intermediate (or more extreme?) CT numbers into
> concentrations.
>
> Method a) assume everything is linear, and just use linear interpolation:
>
> u = (CT-loCT) / (hiCT-loCT)
> CT = loConcentration + (u * (hiConcentration-loConcentration))
>
> I DO NOT RECOMMEND this method!
>
>
> Method b) gather more data - measure CT numbers for known concentrations,
> fit a function to your measurements,
> and evaluate this function at new measured CT numbers.
>
> I might start by measuring the CT number for (loConcentration +
> hiConcentration)/2. If (by some miracle) this turns out to be = (loCT +
> hiCT) / 2, then go to Method a) Otherwise, measure at ¼ and ¾. Continue
> sub-dividing until you are happy with a low-degree polynomial that fits
> your data.
>
> The usual caveats about fitting a predictor to data apply - in
> particular, it is dangerous to EXTRAPOLATE from the measured values.
> Interpolation is much safer. And, avoid high-degree polynomials which may
> overfit your data.
>
> Also consider exponential/log functions. If you know anything about the
> physics of the imaging, use that.
>
> --
> Kenneth Sloan
>
[hidden email]
> Vision is the art of seeing what is invisible to others.
>
>
>
>
> >
> >
> > I am processing a CT image. They have two different brines mixed
> together. One fluid is high CT number. Its concentration is 2mol/L (KI
> doped). Another brine is pure water and its CT number is low.
> >
> > I want to relate the CT number to the concentration value. (Let's
> > assume that the brightest part is 2 mol/L fluid and pure water is
> > lowest CT number)
> >
> > Can anybody help me with the above question?
> >
>
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