Screening of Tuberculosis Using Artificial Neural Network
DOI:
https://doi.org/10.47607/ijresm.2020.392Keywords:
Computer-helped location and finding, Division, Lung design acknowledgment and order, Tuberculosis (TB), X-beam imagingAbstract
Tuberculosis is an infectious bacterial disease that most commonly affects the lungs. This paper reviews, screening of tuberculosis in chest radiograph images using an artificial neural network (ANN). Implementing image processing techniques having segmentation, feature extraction from chest radiographs, at that point building up a fake neural organization for programmed characterization dependent on back proliferation calculation to group tuberculosis accurately. The performance was evaluated using SVM and ANN classifiers regarding exactness, review, and precision. The trial results Confirm the effectiveness of the proposed strategy that gives great Classification proficiency.
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Copyright (c) 2020 A. Anand Kumar, T. Mani, S. Gokulnath, S. K. Kabilesh, K. Dinakaran, A. Stephen Sagayaraj
This work is licensed under a Creative Commons Attribution 4.0 International License.