Automated Tuberculosis Diagnosis Using Fluorescence Images from a Mobile Microscope

@article{Chang2012AutomatedTD,
  title={Automated Tuberculosis Diagnosis Using Fluorescence Images from a Mobile Microscope},
  author={Jeannette Chang and Pablo Andr{\'e}s Arbel{\'a}ez and Neil Switz and Clay Reber and Asa Tapley and J. Lucian Davis and Adithya Cattamanchi and Daniel Fletcher and Jitendra Malik},
  journal={Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention},
  year={2012},
  volume={15 Pt 3},
  pages={345-52}
}
In low-resource areas, the most common method of tuberculosis (TB) diagnosis is visual identification of rod-shaped TB bacilli in microscopic images of sputum smears. We present an algorithm for automated TB detection using images from digital microscopes such as CellScope, a novel, portable device capable of brightfield and fluorescence microscopy. Automated processing on such platforms could save lives by bringing healthcare to rural areas with limited access to laboratory-based diagnostics… CONTINUE READING
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