Login / Signup

Image features for quality analysis of thick blood smears employed in malaria diagnosis.

W M Fong AmarisCarol MartinezLiliana J Cortés-CortésDaniel R Suárez
Published in: Malaria journal (2022)
An analysis of an image-based approach to describe the coloration quality of TBS was presented. It was demonstrated that if a robust background segmentation is conducted, the histogram of the H component from the HSV colour space is the best feature vector to discriminate the coloration quality of the smears. These results are the baseline for automating the estimation of the coloration quality, which has not been studied before, but that can be crucial for automating TBS's analysis for assisting malaria diagnosis process.
Keyphrases
  • deep learning
  • quality improvement
  • machine learning
  • magnetic resonance imaging
  • convolutional neural network
  • diffusion weighted