Searched for: author%3A%22Oyibo%2C+Wellington%22
(1 - 2 of 2)
document
Oyibo, P.O. (author), Agbana, T.E. (author), van Lieshout, Lisette (author), Oyibo, Wellington (author), Diehl, J.C. (author), Vdovin, Gleb (author)
Traditionally, automated slide scanning involves capturing a rectangular grid of field-of-view (FoV) images which can be stitched together to create whole slide images, while the autofocusing algorithm captures a focal stack of images<br/>to determine the best in-focus image. However, these methods can be timeconsuming due to the need for X-, Y-...
journal article 2024
document
Oyibo, P.O. (author), Meulah, Brice (author), Bengtson, Michel (author), Lieshout, Lisette van (author), Oyibo, Wellington (author), Diehl, J.C. (author), Vdovin, Gleb (author), Agbana, T.E. (author)
Purpose: Automated diagnosis of urogenital schistosomiasis using digital microscopy images of urine slides is an essential step toward the elimination of schistosomiasis as a disease of public health concern in Sub-Saharan African countries. We create a robust image dataset of urine samples obtained from field settings and develop a two-stage...
journal article 2023