Abstract
When developing a program to automate an image analysis task, one does not start with a blank slate. Far from it. Many useful algorithms have been described in the literature, and implemented countless times. When developing an image analysis program, experience points the programmer to one or several of these algorithms. The programmer then needs to try out various possible combinations of algorithms before finding a satisfactory solution. Having to implement these algorithms just to see if they work for this one particular application does not make much sense. This is the reason programmers and researches build up libraries of routines that they have implemented in the past, and draw on these libraries to be able to quickly string together a few algorithms and see how they work on the current application. Several image analysis packages exist, both commercial and free, and they can be used as a basis for building up such a library. None of these packages will contain all the necessary algorithms, but they should provide at least the most basic ones. This chapter introduces you to one such package, DIPimage, and demonstrates how one can proceed to quickly develop a solution to automate a routine medical task. As an illustrative example we use some of the approaches taken over the years to solve the long-standing classical medical image analysis problem of assessing a Pap smear. To make best use of this chapter, you should have MATLAB and DIPimage running on your computer, and try out the command sequences given.
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Notes
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You can obtain this file from http://www.cb.uu.se/~cris/Images/papsmear.tif
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Hendriks, C.L.L., Malm, P., Bengtsson, E. (2011). Rapid Prototyping of Image Analysis Applications. In: Dougherty, G. (eds) Medical Image Processing. Biological and Medical Physics, Biomedical Engineering. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9779-1_2
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