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Memorias de investigación
Communications at congresses:
Malaria Cell Counting Diagnosis within Large Field of View
Year:2010
Research Areas
  • Processing and signal analysis
Information
Abstract
Malaria is one of the most serious parasitic infections of human. The accurate and timely diagnosis of malaria infection is essential to control and cure the disease. Some image processing algorithms to automate the diagnosis of malaria on thin blood smears are developed, but the percentage of parasitaemia is often not as precise as manual count. One reason resulting in this error is ignoring the cells at the borders of images. In order to solve this problem, a kind of diagnosis scheme within large field of view (FOV) is proposed. It includes three steps. The first step is image mosaicing to obtain large FOV based on space-time manifolds. The second step is the segmentation of erythrocytes where an improved Hough Transform is used. The third step is the detection of nucleated components. At last, it is concluded that the counting accuracy of malaria infection within large FOV is finer than several regular FOVs
International
Si
Congress
Digital Image Computing: Techniques and Applications DICTA 2010
960
Place
Sydney, Australia
Reviewers
Si
ISBN/ISSN
978-0-7695-4271-3
10.1109/DICTA.2010.40
Start Date
01/12/2010
End Date
03/12/2010
From page
172
To page
177
Proc. Digital Image Computing: Techniques and Applications DICTA 2010
Participants
  • Autor: Narciso Garcia Santos (UPM)
  • Participante: Li-hui Zou (Beijing Institute of Technology)
  • Participante: Jie Chen (Beijing Institute of Technology)
  • Participante: Juan Zhang (Beijing Institute of Technology)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Tratamiento de Imágenes (GTI)
  • Departamento: Señales, Sistemas y Radiocomunicaciones
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