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allied
academies
Microbiology: Current Research
Volume 2
International Conference on
Emerging Diseases, Outbreaks & Case Studies
&
16
th
Annual Meeting on
March 28-29, 2018 | Orlando, USA
Influenza
T
he objective of the study is to improve detection
of pulmonary and pleural abnormalities caused by
pneumonia or tuberculosis (TB) in digital chest X-rays (CXRs).
Amethod was developed and tested by combining shape and
texture features based on which CXRs are classified into two
categories: TB and non-TB cases. Based on observation, we
found that radiologist interpretation is typically comparative
between left and right lung fields, the algorithm uses shape
features to describe the overall geometrical characteristics
of the lung fields and texture features to represent image
characteristics inside them. Our algorithm was evaluated
on two different datasets containing tuberculosis and
pneumonia cases. Using our proposed algorithm, we were
able to increase the overall performance, measured as area
under the (ROC) curve (AUC) by 2.4% over our previous work.
e:
santosh.kc@usd.eduCombination of texture and shape features to detect pulmonary abnormalities in digital chest X-rays
K C Santosh
University of South Dakota, USA