Hier finden Sie wissenschaftliche Publikationen aus den Fraunhofer-Instituten.

Mobile-based analysis of malaria-infected thin blood smears: Automated species and life cycle stage determination

: Rosado, Luis; Correia da Costa, José M.; Elias, Dirk; Cardoso, Jaime S.

Fulltext (PDF; )

Sensors. Online journal 17 (2017), No.10, Art. 2167, 22 pp.
ISSN: 1424-8220
ISSN: 1424-8239
ISSN: 1424-3210
Journal Article, Electronic Publication
Fraunhofer AICOS ()
image analysis; malaria; Computer Aided Diagnosis; microscopy; mobile device

Microscopy examination has been the pillar of malaria diagnosis, being the recommended procedure when its quality can be maintained. However, the need for trained personnel and adequate equipment limits its availability and accessibility in malaria-endemic areas. Rapid, accurate, accessible diagnostic tools are increasingly required, as malaria control programs extend parasite-based diagnosis and the prevalence decreases. This paper presents an image processing and analysis methodology using supervised classification to assess the presence of malaria parasites and determine the species and life cycle stage in Giemsa-stained thin blood smears. The main differentiation factor is the usage of microscopic images exclusively acquired with low cost and accessible tools such as smartphones, a dataset of 566 images manually annotated by an experienced parasilogist being used. Eight different species-stage combinations were considered in this work, with an automatic detection performance ranging from 73.9% to 96.2% in terms of sensitivity and from 92.6% to 99.3% in terms of specificity. These promising results attest to the potential of using this approach as a valid alternative to conventional microscopy examination, with comparable detection performances and acceptable computational times.