|
Título:
|
Counting Malaria parasites with a two-stage EM based algorithm using crowdsourced data
|
|
Autor/a:
|
Cabrera-Bean, Margarita; Pagès Zamora, Alba Maria; Diaz Vilor, Carles; Postigo Camps, Maria; Cuadrado Sánchez, Daniel; Luengo Oroz, Miguel Ángel
|
|
Otros autores:
|
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions |
|
Abstract:
|
Malaria eradication of the worldwide is currently one of the main WHO’s global goals. In this work, we focus on the use of human-machine interaction strategies for lowcost fast reliable malaria diagnostic based on a crowdsourced approach. The addressed technical problem consists in detecting spots in images even under very harsh conditions when positive objects are very similar to some artifacts. The clicks or tags delivered by several annotators labeling an image are modeled as a robust finite mixture, and techniques based on the Expectation-Maximization (EM) algorithm are proposed for accurately counting malaria parasites on thick blood smears obtained by microscopic Giemsa-stained techniques. This approach outperforms other traditional methods as it is shown through experimentation with real data. |
|
Abstract:
|
Peer Reviewed |
|
Materia(s):
|
-Àrees temàtiques de la UPC::Ciències de la salut::Medicina::Medicina comunitària i salut pública
-Àrees temàtiques de la UPC::Enginyeria biomèdica
-Malaria -- Prevention
-Biomedical engineering
-Crowdsourcing
-Malaria thick smear
-EM algorithm
-Robust clustering
-Malaria -- Prevenció
-Enginyeria biomèdica |
|
Derechos:
|
|
|
Tipo de documento:
|
Artículo - Versión publicada
Objeto de conferencia |
|
Editor:
|
Institute of Electrical and Electronics Engineers (IEEE)
|
|
Compartir:
|
|
