ORCA
Online Research @ Cardiff
Browse by Current Cardiff authors
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Up a levelNumber of items: 10.
Oyibo, Prosper  ORCID: https://orcid.org/0000-0003-4316-0883, Meulah, Brice, Agbana, Temitope, van Lieshout, Lisette, Oyibo, Wellington, Vdovine, Gleb and Diehl, Jan Carel
2025.
Deep learning-based automated detection and multiclass classification of soil-transmitted helminths and Schistosoma mansoni eggs in fecal smear images.
Scientific Reports
15
(1)
, 21495.
10.1038/s41598-025-02755-9
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Oyibo, Prosper ORCID: https://orcid.org/0000-0003-4316-0883, Kim, Keun Woo, Hargreaves, Sarah, Wheeler, Philip, Woodley, Owain, Rackley, Thomas, Evans, Mererid and Spezi, Emiliano ORCID: https://orcid.org/0000-0002-1452-8813
2025.
3D DeepLab-based automated GTV segmentation in head and neck cancer using PET/CT imaging.
Presented at: ESTRO 2025,
Vienna, Austria,
2 - 6 May 2025.
Radiotherapy and Oncology.
, vol.206
Elsevier,
S2536-S2538.
10.1016/S0167-8140(25)01892-4
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Oyibo, Prosper ORCID: https://orcid.org/0000-0003-4316-0883, Brynolfsson, Patrik and Spezi, Emiliano ORCID: https://orcid.org/0000-0002-1452-8813
2024.
Integrating radiomic image analysis in the Hero Imaging platform.
Presented at: Cardiff University School of Engineering Research Conference 2024,
Cardiff, UK,
12th - 14th June 2024.
Published in: Spezi, Emiliano and Bray, Michaela eds.
Proceedings of the Cardiff University School of Engineering Research Conference 2024.
Cardiff University Press,
pp. 23-27.
10.18573/conf3.g
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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
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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
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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
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| 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 |
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| 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 |
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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
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| 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 |
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