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Automated image-based diagnosis

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Article from Cris’s Image Analysis Blog

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?

One example where automated systems are routinely used in the clinic (at least in the rich, western world) is for screening for cervical cancer. This is done with the so-called Pap smear since the 1940′s. It takes about 10 minutes to manually examine one smear, which is made on a microscope glass, stained, and looked at through the microscope. Even before digital computers became common, there have been attempts to automate the analysis of the smear. My colleague Ewert Bengtsson wrote his PhD thesis on the subject in 1977, and is still publishing in the field today. This gives an idea of how hard it is to replicate something that is quite easy, though time consuming, for a trained person. The solution, as is often the case, was to change how the sample is prepared. Instead of smearing the sample on a microscope glass, liquid cytology systems were invented that cleaned the sample (removing slime, blood cells, etc.), and produced a neat deposition of cells on the glass such that they are nicely separated and not likely to overlap each other. Such a preparation makes the automated image analysis much easier. However, these automated systems still do not produce a perfect result, and therefore are only approved to be used together with a trained cytologist. That is, the cytologist still needs to review all the tests. This means that the Pap smear test has become more expensive, rather than cheaper (the liquid-based sample preparation uses expensive consumables).

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