dc.contributor |
Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica |
dc.contributor |
González Díez, David |
dc.contributor.author |
Fernández Martínez, Ariadna |
dc.date |
2019-06-10 |
dc.identifier.citation |
PRISMA-143862 |
dc.identifier.uri |
http://hdl.handle.net/2117/176209 |
dc.language.iso |
eng |
dc.publisher |
Universitat Politècnica de Catalunya |
dc.rights |
Attribution-NonCommercial-NoDerivs 3.0 Spain |
dc.rights |
info:eu-repo/semantics/openAccess |
dc.rights |
http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject |
Àrees temàtiques de la UPC::Enginyeria electrònica |
dc.subject |
Microscopes |
dc.subject |
Diagnostic imaging |
dc.subject |
Image processing |
dc.subject |
Microscopis |
dc.subject |
Imatgeria per al diagnòstic |
dc.subject |
Imatges -- Processament |
dc.title |
Project of low-cost microscope automation for data gathering |
dc.type |
info:eu-repo/semantics/bachelorThesis |
dc.description.abstract |
The AiScope is a project of a low-cost microscope that is used to diagnose global diseases in isolated communities. The original microscope is designed to be like any other optical microscope but is built in accessible materials to allow the user to build and use it in any place. This project will consist on the development of the next iteration of the AiScope, which will incorporate an automatic system of sample analysisand image gatheringthat contributes to an easier diagnose of diseases. This system will allow any person with no technical training to use the microscope and obtain the sample images.The automation processwill consist in different parts. The first part will be a software (that will be released open-source in the future) that will determine if the sample is focused or not. This software is based in the border detection image processing technique, that will be explained later in this document and that allows to determine with precision if the sample is focused or not. The second part, the hardware, will consist in a series of moving mechanisms to displace the sample inside the microscope to focus it and obtain images of the whole sample.This hardware will be guided using a Raspberry Pi that will contain the created software.Finally, an Android App to use the system with a mobile phone will be developed.This App will be able to capture the images of the sample and to share information with the microscope.In the end of the project, the user should be allowed to control the microscope with their mobile phone while the microscope focuses and recompiles the images of the sample without any human intervention. However, this will not be the final iteration and many improvements will be needed before its performance is optimal. |