IMAGING - User contributions [en]

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* Main Page @
* AnnotationApp:Main @ [[Main Page|IMAGING]] > AnnotationApp >
* AnnotationApp:Installation and Upgrades @ [[Main Page|IMAGING]] > [[AnnotationApp:Main|AnnotationApp]] >
* AnnotationApp:User Guide @ [[Main Page|IMAGING]] > [[AnnotationApp:Main|AnnotationApp]] >
* AnnotationApp:Backup and Restore @ [[Main Page|IMAGING]] > [[AnnotationApp:Main|AnnotationApp]] >
* Microscope:Main @ [[Main Page|IMAGING]] > Microscope >
* MobileApp:Main @ [[Main Page|IMAGING]] > MobileApp >
* MobileApp:Installation and Upgrades @ [[Main Page|IMAGING]] > [[MobileApp:Main|MobileApp]] >
* MobileApp:User Guide @ [[Main Page|IMAGING]] > [[MobileApp:Main|MobileApp]] >
* MobileApp:Configuring ARIS Bluetooth functionality @ [[Main Page|IMAGING]] > [[MobileApp:Main|MobileApp]] >
* MobileApp:Using ARIS Bluetooth functionality @ [[Main Page|IMAGING]] > [[MobileApp:Main|MobileApp]] >
* MobileApp:Privacy Policy @ [[Main Page|IMAGING]] > [[MobileApp:Main|MobileApp]] >
* MobileApp:Internals @ [[Main Page|IMAGING]] > [[MobileApp:Main|MobileApp]] >
* DataLake:Main @ [[Main Page|IMAGING]] > DataLake >

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IMAGING:About

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<languages/>
<translate>


This project is a joint effort between [https://www.fundacionprobitas.org/en/home ''Fundació Probitas''], [http://www.upc.edu ''Universitat Politècnica de Catalunya'' (UPC)] and [https://vhir.vallhebron.com/en ''Vall d'Hebron Intitut de Recerca'' (VHIR)]. Its general objective is to contribute on the one hand to the achievement of facilitating the diagnosis of malaria and blood parasites such as Chagas disease, and on the other hand, developing an effective, affordable and quality diagnostic system. The aim of the project is to develop a system to reduce underdiagnosis as well as the effort and time required to perform a quality diagnosis. All that at a very low cost and following the official protocols of the health institutions in each country. As a result, the objectives that go beyond the aims of the project are also achieved, such as the creation of a database of labeled images and the development of a low-cost system for obtaining microscopy images.


[[File:LogoProbitas.png|250px|link=https://www.fundacionprobitas.org/en/home]][[File:LogoUPC.png|250px|link=http://www.upc.edu]][[File:LogoVHIR.png|250px|link=https://vhir.vallhebron.com/en]]
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Translations:Main Page/2/es

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IMAGING: Para la mejora de la Salud a través de un diagnóstico rápido, confiable y económico

Main Page

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<languages/>
<translate>

[[Category:Main Page]]


[[File:Imaging-overview.png|500px|right|thumb|Imaging Overview]]


IMAGING: For an improvement of Health through rapid, reliable and economic diagnosis


The [[Global Laboratory Initiative]] (GLI) is a program set up by the [https://www.fundacionprobitas.org/en/home 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 [https://imaging.upc.edu/en 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.


__TOC__

== Analytical requests information system (ARIS) == 
[[ARIS:main|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 == 
[[Microscope:Main|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 === 
The [[MobileApp:Main|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:main|ARIS]].

== Annotation App == 
The [[AnnotationApp:Main|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 == 
The [[DataLake:Main|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.

</translate>

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Main Page

2023-01-29T15:01:45Z

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<languages/>
<translate>

[[Category:Main Page]]


[[File:Imaging-overview.png|500px|right|thumb|Imaging Overview]]


For an improvement of Health through rapid, reliable and economic diagnosis (iH-rred)


The [[Global Laboratory Initiative]] (GLI) is a program set up by the [https://www.fundacionprobitas.org/en/home 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 [https://imaging.upc.edu/en 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.


__TOC__

== Analytical requests information system (ARIS) == 
[[ARIS:main|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 == 
[[Microscope:Main|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 === 
The [[MobileApp:Main|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:main|ARIS]].

== Annotation App == 
The [[AnnotationApp:Main|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 == 
The [[DataLake:Main|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.

</translate>

Main Page/es

2023-01-29T15:01:41Z

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<languages/>
<div lang="en" dir="ltr" class="mw-content-ltr">
[[Category:Main Page]]
</div>

[[File:Imaging-overview.png|500px|right|thumb|Perspectiva general del proyecto de imagenes]]

Para la mejora de la Salud a través de un diagnóstico rápido, confiable y económico (iH-rred)

La [[Global Laboratory Initiative]] (GLI) es un programa lanzado por la [https://www.fundacionprobitas.org/en/home Fundación Probitas Foundation] 2010 con la intención de reforzar las capacidades de diagnóstico clínico en laboratorios de las regiones más vulnerables del mundo.
Como parte de esta gran iniciativa, Probitas promovió una [https://imaging.upc.edu/es iniciativa para crear una plataforma de automatización del diagnóstico de Malaria y Enfermedades Tropicales Desatendidas (NTDs, por sus siglas en Inglés)]. Esta página contiene información describiendo las diferentes tecnologías ''hardware'' y ''software'' involucradas en dicho proyecto.

__TOC__

== Sistema de información para peticiones analíticas (ARIS) ==
[[ARIS:main|ARIS]] es un sistema ''software'' de gestión y análisis básico de datos laboratorios relacionados con pacientes, peticiones, diagnósticos y tests de análisis.
Ofrece funcionalidades básicas con una interficie que puede configurarse de forma flexible para dar soporte a las principales tareas de un pequeño laboratorio.

== Microscopio con autofoco ==
[[Microscope:Main|Microscopio con autofoco]] es un conjunto de piezas ''hardware'' conectadas a un motor tipo Arduíno que automatiza la captura de imágenes de las muestras.
Un teléfono móvil controla el movimiento de la placa, y después de un breve instante, la toma de fotografías.

=== Aplicación móvil ===
La [[MobileApp:Main|Aplicación móvil]] es una aplicación de ''software'' abierto para controlar los motores Arduino que mueven la placa y enfocan el ocular, al mismo tiempo que toman fotografías de la muestra automáticamente.
Posteriormente, las imagenes tomadas desde el móvil pueden descargarse en la aplicatión de escritorio [[ARIS:main|ARIS]].

<div lang="en" dir="ltr" class="mw-content-ltr">
== Annotation App ==
The [[AnnotationApp:Main|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.
</div>

<div lang="en" dir="ltr" class="mw-content-ltr">
== Annotated images Data Lake ==
The [[DataLake:Main|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.
</div>

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=== Aplicación móvil ===
La [[MobileApp:Main|Aplicación móvil]] es una aplicación de ''software'' abierto para controlar los motores Arduino que mueven la placa y enfocan el ocular, al mismo tiempo que toman fotografías de la muestra automáticamente.
Posteriormente, las imagenes tomadas desde el móvil pueden descargarse en la aplicatión de escritorio [[ARIS:main|ARIS]].

Translations:Main Page/6/es

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== Microscopio con autofoco ==
[[Microscope:Main|Microscopio con autofoco]] es un conjunto de piezas ''hardware'' conectadas a un motor tipo Arduíno que automatiza la captura de imágenes de las muestras.
Un teléfono móvil controla el movimiento de la placa, y después de un breve instante, la toma de fotografías.

Main Page

2023-01-29T15:00:06Z

Wikiroot: Marked this version for translation

<languages/>
<translate>

[[Category:Main Page]]


[[File:Imaging-overview.png|500px|right|thumb|Imaging Overview]]


For an improvement of Health through rapid, reliable and economic diagnosis (iH-rred)


The [[Global Laboratory Initiative]] (GLI) is a program set up by the [https://www.fundacionprobitas.org/en/home 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 [https://imaging.upc.edu/en 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.


__TOC__

== Analytical requests information system (ARIS) == 
[[ARIS:main|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 == 
[[Microscope:Main|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 === 
The [[Mobile App:Main|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:main|ARIS]].

== Annotation App == 
The [[AnnotationApp:Main|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 == 
The [[DataLake:Main|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.

</translate>

Main Page

2023-01-29T14:57:34Z

Wikiroot:

<languages/>
<translate>
[[Category:Main Page]]


[[File:Imaging-overview.png|500px|right|thumb|Imaging Overview]]


For an improvement of Health through rapid, reliable and economic diagnosis (iH-rred)


The [[Global Laboratory Initiative]] (GLI) is a program set up by the [https://www.fundacionprobitas.org/en/home 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 [https://imaging.upc.edu/en 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.


__TOC__

== Analytical requests information system (ARIS) == 
[[ARIS:main|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 == 
[[Microscope:Main|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 === 
The [[Mobile App:Main|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:main|ARIS]].

== Annotation App == 
The [[AnnotationApp:Main|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 == 
The [[DataLake:Main|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.

</translate>

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DataLake:Main

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[[Category:DataLake:Main]]

'''UNDER CONSTRUCTION'''

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'''UNDER CONSTRUCTION'''

MobileApp:Main

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'''UNDER CONSTRUCTION'''

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[[Category:Images:Mobile App]]

'''UNDER CONSTRUCTION'''

Microscope:Main

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'''UNDER CONSTRUCTION'''

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[[Category:Images:Data Lake]]

'''UNDER CONSTRUCTION'''

AnnotationApp:Main

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[[Category:AnnotationApp:Main]]

Annotation App is a tool developed to support the process of annotating microscopic images of blood samples. It offers basic functionalities to highlight parts of the image and label them using pre-defined annotations. For instance, in the case of Malaria one can mark the different kinds of parasites appearing in the image and label them. The result of the labeling allows the creation of a training dataset that can be used to train machine learning models.

==Installation and Upgrades==

The [[AnnotationApp:Installation and Upgrades|Installation and Upgrades]] page

==User Guide==

The [[AnnotationApp:User Guide|User Guide]] page

==Backup and Restore==

The [[AnnotationApp:Backup and Restore|Backup and Restore]] page

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[[Category:AnnotationApp:Backup and Restore]]

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[[Category:Annotation App:Backup and Restore]]

AnnotationApp:Main

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AnnotationApp:Installation and Upgrades

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[[Category:AnnotationApp:Installation and Upgrades]]

This is a step-by-step installation guide for the Annotation App.

== Pre-requisites ==
#Internet connection: In order to work with the Annotation App you need to be connected to the Internet at all times.
#Python 3: The Annotation App is developed in Python 3, thus you need to have it installed in your computer to work with it. See below how to [[Images:Annotation_App#Install Python 3#|install Python 3]].
#Annotation App: You need to download the Annotation App to your local file system. See below how to [[Images:Annotation_App#Download and run Annotation App| download and run the Annotation App]].

== Install Python 3 ==
# Download the Windows installer for Python 3 using the following link:
#* https://www.python.org/ftp/python/3.8.7/python-3.8.7-amd64.exe
# Double click on the downloaded file to start the installation process. You will be prompted with the following screenshot:
#* Make sure to click on the check boxes: "Install launcher for all users" and "Add Python 3.8 to PATH".
#*;[[File:Python-installation-screenshot.png]]
# Click on "Install Now" and follow the steps until you are confirmed that the installation has been completed successfully.
#* In case of issues refer to this [https://www.python.org/downloads/windows/ page] for more help.

== Download and run the Annotation App ==
Follow the instructions below to download and start the AnnotationApp
#Download the AnnotationApp using the following link:
#*https://github.com/dtim-upc/IMAGING
#*Click on "Code" and then "Download ZIP" as shown in the screenshot below.
#*;[[File:Annotationapp-download-screenshot.png]]
#Unzip the downloaded file to your preferred location.
#*Right click on top of the file and click "Extract here".
#Double-click on the unzipped folder and enter the "AnnotationApp" folder.
#*[ONLY IN THE VERY FIRST USE OF THE APP] Double-click on the "install-reqired-libraries.bat" program to install the necessary libraries. This operation needs to be performed only once.
#Run the AnnotationApp double-clicking on the program "start-AnnotationApp.bat"

AnnotationApp:Installation and Upgrades

2023-01-29T14:50:44Z

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[[Category:Annotation App:Installation and Upgrades]]

This is a step-by-step installation guide for the Annotation App.

== Pre-requisites ==
#Internet connection: In order to work with the Annotation App you need to be connected to the Internet at all times.
#Python 3: The Annotation App is developed in Python 3, thus you need to have it installed in your computer to work with it. See below how to [[Images:Annotation_App#Install Python 3#|install Python 3]].
#Annotation App: You need to download the Annotation App to your local file system. See below how to [[Images:Annotation_App#Download and run Annotation App| download and run the Annotation App]].

== Install Python 3 ==
# Download the Windows installer for Python 3 using the following link:
#* https://www.python.org/ftp/python/3.8.7/python-3.8.7-amd64.exe
# Double click on the downloaded file to start the installation process. You will be prompted with the following screenshot:
#* Make sure to click on the check boxes: "Install launcher for all users" and "Add Python 3.8 to PATH".
#*;[[File:Python-installation-screenshot.png]]
# Click on "Install Now" and follow the steps until you are confirmed that the installation has been completed successfully.
#* In case of issues refer to this [https://www.python.org/downloads/windows/ page] for more help.

== Download and run the Annotation App ==
Follow the instructions below to download and start the AnnotationApp
#Download the AnnotationApp using the following link:
#*https://github.com/dtim-upc/IMAGING
#*Click on "Code" and then "Download ZIP" as shown in the screenshot below.
#*;[[File:Annotationapp-download-screenshot.png]]
#Unzip the downloaded file to your preferred location.
#*Right click on top of the file and click "Extract here".
#Double-click on the unzipped folder and enter the "AnnotationApp" folder.
#*[ONLY IN THE VERY FIRST USE OF THE APP] Double-click on the "install-reqired-libraries.bat" program to install the necessary libraries. This operation needs to be performed only once.
#Run the AnnotationApp double-clicking on the program "start-AnnotationApp.bat"

AnnotationApp:Main

2023-01-29T14:50:19Z

Wikiroot:

[[Category:AnnotationApp:Main]]

Annotation App is a tool developed to support the process of annotating microscopic images of blood samples. It offers basic functionalities to highlight parts of the image and label them using pre-defined annotations. For instance, in the case of Malaria one can mark the different kinds of parasites appearing in the image and label them. The result of the labeling allows the creation of a training dataset that can be used to train machine learning models.

==Installation and Upgrades==

The [[Annotation App:Installation and Upgrades|Installation and Upgrades]] page

==User Guide==

The [[AnnotationApp:User Guide|User Guide]] page

==Backup and Restore==

The [[Annotation App:Backup and Restore|Backup and Restore]] page

AnnotationApp:User Guide

2023-01-29T14:49:44Z

Wikiroot:

[[Category:AnnotationApp:User Guide]]

This is a step-by-step user guide for the Annotation App. It contains information on what each feature does and instructions on how to use them.

== Application layout (GUI) ==

The application is composed of a single window, whose elements are depicted in the image below:
;[[File:Annotationapp-0.0.1-screenshot.png]]

== Application usage ==

The tool supports loading multiple images, which allows to annotate a set of images and later save all the pending changes. To do so, the annotator must select multiple input files.

;[[File:Image_here.png]]

If an image has already been annotated, its annotations will be automatically loaded. Otherwise, an empty set of annotations will be displayed. When the annotator updates the current set of annotations, the tool will inform that the changes are not synchronized with the cloud using the following icons:
* Changes have been stored [icon missing]
* Changes have not been stored [icon missing]

It is recommended to periodically save pending annotations. Also, in order to avoid the loss of data in the presence of application errors, avoid annotating in parallel a large set of images.

The process of generating annotations is performed graphically over the image. The annotator must accurately select the area (bounding box) of each potential parasite (either positive, negative or uncertain) as follows:

;[[File:Image_here.png]]
Generating annotations will not be possible if the annotator has not selected the kind of parasite, the label (positive, negative, or uncertain) and the kind of sample.
After saving, either a single image or a set of images, the application will inform of the successful storage. At this moment, the system has synchronized all the changes with the cloud repository. Nevertheless, it is important also to know that upon the loss of internet connection or any other error related to the synchronization with the cloud, the system locally maintains the files in an internal folder.


;[[File:Image_here.png]]

AnnotationApp:User Guide

2023-01-29T14:49:14Z

Wikiroot: Wikiroot moved page Annotation App:User Guide to AnnotationApp:User Guide without leaving a redirect

[[Category:Annotation App:User Guide]]

This is a step-by-step user guide for the Annotation App. It contains information on what each feature does and instructions on how to use them.

== Application layout (GUI) ==

The application is composed of a single window, whose elements are depicted in the image below:
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== Application usage ==

The tool supports loading multiple images, which allows to annotate a set of images and later save all the pending changes. To do so, the annotator must select multiple input files.

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If an image has already been annotated, its annotations will be automatically loaded. Otherwise, an empty set of annotations will be displayed. When the annotator updates the current set of annotations, the tool will inform that the changes are not synchronized with the cloud using the following icons:
* Changes have been stored [icon missing]
* Changes have not been stored [icon missing]

It is recommended to periodically save pending annotations. Also, in order to avoid the loss of data in the presence of application errors, avoid annotating in parallel a large set of images.

The process of generating annotations is performed graphically over the image. The annotator must accurately select the area (bounding box) of each potential parasite (either positive, negative or uncertain) as follows:

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Generating annotations will not be possible if the annotator has not selected the kind of parasite, the label (positive, negative, or uncertain) and the kind of sample.
After saving, either a single image or a set of images, the application will inform of the successful storage. At this moment, the system has synchronized all the changes with the cloud repository. Nevertheless, it is important also to know that upon the loss of internet connection or any other error related to the synchronization with the cloud, the system locally maintains the files in an internal folder.


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