Development of an automated artificial intelligence-based system for urogenital schistosomiasis diagnosis using digital image analysis techniques and a robotized microscope
The development of low-cost novel diagnostic techniques based on the detection and identification of S. haematobium eggs in urine by AI tools would be a suitable alternative to conventional microscopy in non-endemic settings. This technical proof-of-principle study allows laying the basis for improving the system, and optimizing its implementation in the laboratories.
Authors
- Daniel López (ORCID: https://orcid.org/0000-0002-0408-4526)
- Tomàs Pumarola (ORCID: https://orcid.org/0000-0002-5171-7461)
- Sergi Nadal (ORCID: https://orcid.org/0000-0002-8565-952X)
- Elisa Sayrol
- Edurne Ruiz
- Elena Sulleiro (ORCID: https://orcid.org/0000-0002-9783-6060)
- Alejandro Mediavilla (ORCID: https://orcid.org/0009-0000-5273-9251)
- Carles Rubio Maturana (ORCID: https://orcid.org/0000-0002-5615-9278)
- Joan Joseph-Munné
- Francesc Zarzuela (ORCID: https://orcid.org/0000-0001-7520-978X)
- Allisson Dantas de Oliveira (ORCID: https://orcid.org/0000-0002-8267-9760)
- Alberto Abelló (ORCID: https://orcid.org/0000-0002-3223-2186)
- Patricia Martínez-Vallejo
Institutions
- Universitat Autònoma de Barcelona (ES)
- Universitat Pompeu Fabra (ES)
- Instituto de Salud Carlos III (ES)
- Vall d'Hebron Institut de Recerca (ES)
- Centro de Investigación Biomédica en Red (ES)
- Universitat Politècnica de Catalunya (ES)
Publication Details
- Journal
- PLoS neglected tropical diseases
- Published
- 2024-11-05
- DOI
- https://doi.org/10.1371/journal.pntd.0012614
- Citations
- 11
- Primary Topic
- Digital Imaging for Blood Diseases
- Type
- article
- Field-Weighted Citation Impact
- 2.74
Funders
- Ministerio de Ciencia e Innovación
- Fundació Institut de Recerca Hospital Universitari Vall d’Hebron
- Universitat Politècnica de Catalunya
- Instituto de Salud Carlos III
- Yitzhak and Chaya Weinstein Research Institute for Signal Processing, Tel Aviv University