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IMAGING: For an improvement of Health through rapid, reliable and economic diagnosis
The Global Laboratory Initiative (GLI) is a program set up by the Probitas Foundation in 2010 with the aim of reinforcing the capacities of clinical diagnostic laboratories in the most vulnerable regions of the world. As part of this big initiative Probitas promoted an initiative to create a platform to automate the diagnosis of Malaria and Neglected tropical diseases (NTDs). This pages contain information describing different hardware and software technologies involved in this project.
Analytical requests information system (ARIS)[edit]
ARIS is a laboratory software system for managing and analyzing data related to patients, requests, diagnostics, and analytical tests. It offers basic functionalities and a simple interface that can be flexibly configured to support the main tasks of a small laboratory.
Autofocus microscope[edit]
Autofocus microscope is a set of hardware pieces connected to an Arduino engine that automate the image capture from samples. A mobile phone controls the movement of the plaque, and eventually get the images of the sample.
Mobile App[edit]
The Mobile App is an open source software application to control the Arduino engines that move the plaque and focus the ocular of the microscope, as well as automatically take pictures of the sample. Eventually, the images taken with the app can be downloaded to the desktop application ARIS.
Annotation App[edit]
The Annotation App is a software tool facilitating the annotation of images to create training datasets. Given an image of a sample, it allows to frame an object and indicate whether it is leucocyte, parasite, etc. Eventually, once we have enough tagged images, these are used to train a Neural Network that can automate the process with high precision.
Annotated images Data Lake[edit]
The Data Lake is a repository of images with their corresponding annotations. This include the management software, as well as the necessary tools to extract some basic statistics and easily download subsets of images that can be used as a training set for Machine Learning.