ORCA
Online Research @ Cardiff

Clear Cookie - decide language by browser settings

Browse by Current Cardiff authors

Number of items: 7.

Oyibo, Prosper, Agbana, Tope, van Lieshout, Lisette, Oyibo, Wellington, Diehl, Jan-Carel and Vdovine, Gleb 2024. An automated slide scanning system for membrane filter imaging in diagnosis of urogenital schistosomiasis. Journal of Microscopy 294 (1) , pp. 52-61. 10.1111/jmi.13269

Meulah, Brice, Oyibo, Prosper, Hoekstra, Pytsje T., Moure, Paul Alvyn Nguema, Maloum, Moustapha Nzamba, Laclong-Lontchi, Romeo Aime, Honkpehedji, Yabo Josiane, Bengtson, Michel, Hokke, Cornelis, Corstjens, Paul L. A. M., Agbana, Temitope, Diehl, Jan Carel, Adegnika, Ayola Akim and van Lieshout, Lisette 2024. Validation of artificial intelligence-based digital microscopy for automated detection of Schistosoma haematobium eggs in urine in Gabon. PLoS Neglected Tropical Diseases 18 (2) , e0011967. 10.1371/journal.pntd.0011967

Oyibo, Prosper, Meulah, Brice, Bengtson, Michel, van Lieshout, Lisette, Oyibo, Wellington, Diehl, Jan-Carel, Vdovine, Gleb and Agbana, Tope 2023. Two-stage automated diagnosis framework for urogenital schistosomiasis in microscopy images from low-resource settings. Journal of Medical Imaging 10 (04) , 044005. 10.1117/1.JMI.10.4.044005

Bengtson, Michel, Onasanya, Adeola, Oyibo, Prosper, Meulah, Brice, Samenjo, Karl Tondo, Braakman, Ingeborg, Oyibo, Wellington and Diehl, J.C. 2022. A usability study of an innovative optical device for the diagnosis of schistosomiasis in Nigeria. Presented at: Global Humanitarian Technology Conference (GHTC), Santa Clara, CA, USA, 8-11 September 2022. Proceedings of Global Humanitarian Technology Conference. IEEE, pp. 17-22. 10.1109/GHTC55712.2022.9911019

Oyibo, Prosper, Jujjavarapu, Satyajith, Meulah, Brice, Agbana, Tope, Braakman, Ingeborg, van Diepen, Angela, Bengtson, Michel, van Lieshout, Lisette, Oyibo, Wellington, Vdovine, Gleb and Diehl, Jan-Carel 2022. Schistoscope: An automated microscope with artificial intelligence for detection of schistosoma haematobium eggs in resource-limited settings. Micromachines 13 (5) , 643. 10.3390/mi13050643

Meulah, Brice, Oyibo, Prosper, Bengtson, Michel, Agbana, Temitope, Lontchi, Roméo Aimé Laclong, Adegnika, Ayola Akim, Oyibo, Wellington, Hokke, Cornelis Hendrik, Diehl, Jan Carel and van Lieshout, Lisette 2022. Performance evaluation of the Schistoscope 5.0 for (semi-)automated digital detection and quantification of schistosoma haematobium eggs in Urine: A field-based study in Nigeria. American Journal of Tropical Medicine and Hygiene 107 (5) , 1047–1054. 10.4269/ajtmh.22-0276

Carel Diehl, Jan, Oyibo, Prosper, Agbana, Temitope, Jujjavarapu, Satyajith, Van, G-Young, Vdovin, Gleb and Oyibo, Wellington 2021. Schistoscope: smartphone versus Raspberry Pi based low-cost diagnostic device for urinary Schistosomiasis. Presented at: 2020 IEEE Global Humanitarian Technology Conference (GHTC), Seattle, 29 October - 1 November 2020. Proceedings of 2020 IEEE Global Humanitarian Technology Conference (GHTC). IEEE, 10.1109/ghtc46280.2020.9342871

This list was generated on Wed May 1 07:38:01 2024 BST.