Abstract
Microscopy for medical diagnostics requires expensive equipment as well as highly trained experts to operate and interpret the observed images. We present a new, easy to use, mobile diagnostic system consisting of a direct imaging microlens array and a mobile computing platform for diagnosing parasites in clinical samples. Firstly, the captured microlens images are reconstructed using a light field rendering method. Then, OpenCL accelerated classification utilizing local binary pattern features is performed. A speedup of factor 4.6 was achieved for the mobile computing platform CPU (AMD C-50) compared with the GPU (AMD 6250). The results show that a relatively inexpensive system can be used for automatically detecting eggs of the Schistosoma parasite. Furthermore, the system can be also used to diagnose other parasites and thinlayer microarray samples containing stained tumor cells.
The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-3-319-02895-8_64
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Varjo, S., Hannuksela, J. (2013). A Mobile Imaging System for Medical Diagnostics. In: Blanc-Talon, J., Kasinski, A., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2013. Lecture Notes in Computer Science, vol 8192. Springer, Cham. https://doi.org/10.1007/978-3-319-02895-8_20
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DOI: https://doi.org/10.1007/978-3-319-02895-8_20
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