Computer-aided detection of pulmonary tuberculosis and pulmonary cavity on adult chest radiographs using a region convolutional neural network.
- Author:
Kevin Eric R. Santos
1
Author Information
- Publication Type:Journal Article
- Keywords: Pulmonary;
- MeSH: Tuberculosis, Pulmonary; Sensitivity and Specificity; Neural Networks (Computer); Software
- From: Journal of the Philippine Medical Association 2020;99(1):10-21
- CountryPhilippines
- Language:English
-
Abstract:
OBJECTIVES:To train and evaluate the performance
of a detector for pulmonary tuberculosis and
pulmonary cavity, using the Faster Region
Convolutional Neural Network model.
STUDY DESIGN:A cross-sectional study design was employed to describe the sensitivity, specificity, and accuracy of the Faster Region Convolutional Neural Network model for the detection of pulmonary tuberculosis and pulmonary cavity.
SUBJECTS:Radiographs for the training dataset and testing dataset were acquired from the Picture Archiving and Communication System of the a general public hospital in Quezon City.
SETTING:The setting of the study is a general public hospital in Quezon City, Philippines.
OUTCOMES:The detector for pulmonary tuberculosis and pulmonary cavity was trained with the training dataset using the TensorFlow machine learning library, with the Faster-RCNN-lnception-V2 used as the base model. Detector findings on the testing dataset were compared and analyzed against findings of three board-certified radiologists.
RESULTS:The detector achieved 92.11 % sensitivity, 87.1 % specificity, and 89% accuracy as a screening tool, and 84.04% sensitivity, 98.04% specificity, and 95.87% accuracy, as a locator of pulmonary tuberculosis and cavity.
CONCLUSION:This study is the first of its kind to demonstrate the feasibility of training a detector for pulmonary tuberculosis and pulmonary cavities using the Region Convolutional Neural Network model. Limitations and improvements to the detector may be addressed in future research. - Full text:Computer-aided detection of pulmonary tuberculosis.pdf
