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2022 | 2 |
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Page 1
Two-stage automated diagnosis framework for urogenital schistosomiasis in microscopy images from low-resource settings.
J Med Imaging (Bellingham). 2023 Jul;10(4):044005. doi: 10.1117/1.JMI.10.4.044005. Epub 2023 Aug 7.
J Med Imaging (Bellingham). 2023.
PMID: 37554627
Schistoscope: An Automated Microscope with Artificial Intelligence for Detection of Schistosoma haematobium Eggs in Resource-Limited Settings.
Oyibo P, Jujjavarapu S, Meulah B, Agbana T, Braakman I, van Diepen A, Bengtson M, van Lieshout L, Oyibo W, Vdovine G, Diehl JC.
Oyibo P, et al.
Micromachines (Basel). 2022 Apr 19;13(5):643. doi: 10.3390/mi13050643.
Micromachines (Basel). 2022.
PMID: 35630110
Free PMC article.
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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.
Meulah B, Oyibo P, Bengtson M, Agbana T, Lontchi RAL, Adegnika AA, Oyibo W, Hokke CH, Diehl JC, van Lieshout L.
Meulah B, et al. Among authors: oyibo p.
Am J Trop Med Hyg. 2022 Oct 17;107(5):1047-1054. doi: 10.4269/ajtmh.22-0276. Print 2022 Nov 14.
Am J Trop Med Hyg. 2022.
PMID: 36252803
Free PMC article.
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An automated slide scanning system for membrane filter imaging in diagnosis of urogenital schistosomiasis.
Oyibo P, Agbana T, van Lieshout L, Oyibo W, Diehl JC, Vdovine G.
Oyibo P, et al.
J Microsc. 2024 Apr;294(1):52-61. doi: 10.1111/jmi.13269. Epub 2024 Jan 30.
J Microsc. 2024.
PMID: 38291833
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Validation of artificial intelligence-based digital microscopy for automated detection of Schistosoma haematobium eggs in urine in Gabon.
Meulah B, Oyibo P, Hoekstra PT, Moure PAN, Maloum MN, Laclong-Lontchi RA, Honkpehedji YJ, Bengtson M, Hokke C, Corstjens PLAM, Agbana T, Diehl JC, Adegnika AA, van Lieshout L.
Meulah B, et al. Among authors: oyibo p.
PLoS Negl Trop Dis. 2024 Feb 23;18(2):e0011967. doi: 10.1371/journal.pntd.0011967. eCollection 2024 Feb.
PLoS Negl Trop Dis. 2024.
PMID: 38394298
Free PMC article.
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