Proper counting

September 23rd, 2014

I just came across an editorial in the Journal of the American Society of Nephrology (Kirsten M. Madsen, Am Soc Nephrol 10(5):1124-1125, 1999), which states:

A considerable number of manuscripts submitted to the Journal include quantitative morphologic data based on counts and measurements of profiles observed in tissue sections or projected images. Quite often these so-called morphometric analyses are based on assumptions and approximations that cannot be verified and therefore may be incorrect. Moreover, many manuscripts have insufficient descriptions of the sampling procedures and statistical analyses in the Methods section, or it is apparent that inappropriate (biased) sampling techniques were used. Because of the availability today of many new and some old stereologic methods and tools that are not based on undeterminable assumptions about size, shape, or orientation of structures, the Editors of the Journal believe that it is time to dispense with the old, often biased, model-based stereology and change the way we count and measure.

It then goes on to say that the journal would require appropriate stereological methods be employed for quantitative morphologic studies. I have never read a paper in this journal, but certainly hope that they managed to hold on to this standard during the 15 years since this editorial was written. Plenty of journals have not come this far yet.

DIPimage 2.6 released

April 14th, 2014

Today we released version 2.6 of DIPimage and DIPlib. The change list is rather short. There are two items that I think are important: 1) We fixed a bug that caused an unnecessary copy of the output image(s) in the DIPlib-MEX interface, slowing down functions especially for large images. 2) We introduced a new setting to automatically make use of a feature introduced in the previous release.

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On interpolation

January 4th, 2014

Last month I asked the following question in an exam for the advanced image analysis course we teach here: “Given that interpolation is a convolution, describe how you would compute an interpolation using the Fourier Transform.” Unfortunately I can count on one finger the number of students that did not simply answer with something in the order of “convolution can be computed by multiplication in the Fourier domain.” And the one student that did not give this answer didn’t give an answer at all… Apparently this question is too difficult, though I thought it was interesting and only mildly challenging. In this post I’ll discuss interpolation and in passing give the correct answer to this question.

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DIPimage 2.5.1 released

October 4th, 2013

We recently released a bugfix for DIPimage release 2.5. Since I didn’t announce the release of 2.5 here, this might be a good opportunity to review some of the improvements in 2.5.

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Automated image-based diagnosis

August 24th, 2013

Nowhere is it as difficult to get a fully automatic image analysis system accepted and used in practice as in the clinic. Not only are physicians sceptical of technology that makes them irrelevant, but an automated system has to produce a perfect result, a correct diagnosis for 100% of the cases, to be trusted without supervision. And of course this is impossible to achieve. In fact, even if the system has a better record than an average (or a good) physician, it is unlikely that it is the same cases where the system and the physician are wrong. Therefore, the combination of machine + physician is better than the machine, and thus the machine should not be used without the physician.

What often happens then is that the system is tuned to yield a near 100% sensitivity (to miss only very few positives), and thus has a very low specificity (that is, it marks a lot of negative tests as positive). The system is heavily biased to the positives. The samples marked by the system as negative are almost surely negative, whereas the samples marked as positive (or, rather, suspect) are reviewed by the physician. This is supposed to lighten the workload of the physician. This seems nice and useful, no? What is the problem?

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