Two-stage automated diagnosis framework for urogenital schistosomiasis in microscopy images from low-resource settings.

Prosper Oyibo Brice MeulahMichel BengtsonLisette van LieshoutWellington OyiboJan-Carel DiehlGleb VdovineTope Agbana

Published in: Journal of medical imaging (Bellingham, Wash.) (2023)

Our detection framework is a promising tool for the diagnosis of urogenital schistosomiasis as our results meet the World Health Organization target product profile requirements for monitoring and evaluation of schistosomiasis control programs.

Keyphrases

deep learning
high throughput
optical coherence tomography
label free
machine learning
public health
high resolution
single molecule
convolutional neural network
high speed
loop mediated isothermal amplification
single cell