\(\mu \)SmartScope: Towards a Fully Automated 3D-Printed Smartphone Microscope with Motorized Stage
Microscopic examination is the reference diagnostic method for several neglected tropical diseases. However, its quality and availability in rural endemic areas is often limited by the lack of trained personnel and adequate equipment. These drawbacks are closely related with the increasing interest in the development of computer-aided diagnosis systems, particularly distributed solutions that provide access to complex diagnosis in rural areas. In this work we present our most recent advances towards the development of a fully automated 3D-printed smartphone microscope with a motorized stage, termed \(\mu \)SmartScope. The developed prototype allows autonomous acquisition of a pre-defined number of images at 1000x magnification, by using a motorized automated stage fully powered and controlled by a smartphone, without the need of manual focus. In order to validate the prototype as a reliable alternative to conventional microscopy, we evaluated the \(\mu \)SmartScope performance in terms of: resolution; field of view; illumination; motorized stage performance (mechanical movement precision/resolution and power consumption); and automated focus. These results showed similar performances when compared with conventional microscopy, plus the advantage of being low-cost and easy to use, even for non-experts in microscopy. To extract these results, smears infected with blood parasites responsible for the most relevant neglected tropical diseases were used. The acquired images showed that it was possible to detect those agents through images acquired via the \(\mu \)SmartScope, which clearly illustrate the huge potential of this device, specially in developing countries with limited access to healthcare services.
KeywordsMicroscopy Mobile devices Motorized microscope stage Developing countries Mobile health
We would like to acknowledge the financial support from North Portugal Regional Operational Programme (NORTE 2020), Portugal 2020 and the European Regional Development Fund (ERDF) from European Union through the project ‘Deus ex Machina: Symbiotic Technology for Societal Efficiency Gains’, NORTE-01-0145-FEDER-000026.
- 1.The END Fund: NTD Overview. http://www.end.org/whatwedo/ntdoverview. Accessed 11 Sept 2017
- 2.Utzinger, J., Becker, S.L., Knopp, S., Blum, J., Neumayr, A.L., Keiser, J., Hatz, C.F.: Neglected tropical diseases: diagnosis, clinical management, treatment and control. Swiss Med. Weekly 142 (2012)Google Scholar
- 7.Rosado, L., da Costa, J.M.C., Elias, D., Cardoso, J.S.: A review of automatic malaria parasites detection and segmentation in microscopic images. 14(1), 11–22 (2016). http://www.eurekaselect.com
- 8.Rosado, L., Oliveira, J., Vasconcelos, M.J.M., da Costa, J.M.C., Elias, D., Cardoso, J.S.: \(\mu \)SmartScope: 3D-printed smartphone microscope with motorized automated stage. In: Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIODEVICES, (BIOSTEC 2017), pp. 38–48. INSTICC, SciTePress (2017)Google Scholar
- 11.Arpa, A., Wetzstein, G., Lanman, D., Raskar, R.: Single lens off-chip cellphone microscopy, pp. 23–28. IEEE, June 2012Google Scholar
- 15.WHO: Basic malaria microscopy. Number Part 1. World Health Organization (1991)Google Scholar
- 16.Budynas, R.G., Nisbett, K.J.: Shigley’s Mechanical Engineering Design, 10th edn. McGraw-Hill Education, New York (2014)Google Scholar
- 17.Wakerly, M.: USB Serial for Android (2012)Google Scholar
- 19.Shih, L.: Autofocus survey: a comparison of algorithms. In: Electronic Imaging 2007, International Society for Optics and Photonics, p. 65020B (2007)Google Scholar
- 20.Sun, Y., Duthaler, S., Nelson, B.J.: Autofocusing algorithm selection in computer microscopy. In: 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 70–76. IEEE (2005)Google Scholar
- 22.Tenenbaum, J.M.: Accommodation in computer vision. Ph.D. dissertation. Technical report, DTIC Document (1970)Google Scholar