Efficient Deep Network Architectures for Fast Chest X-Ray Tuberculosis Screening and Visualization.
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ABSTRACT:
SUBMITTER: Pasa F
PROVIDER: S-EPMC6472370 | biostudies-literature | 2019 Apr
REPOSITORIES: biostudies-literature
Publications
Efficient Deep Network Architectures for Fast Chest X-Ray Tuberculosis Screening and Visualization.
Pasa F F Golkov V V Pfeiffer F F Cremers D D Pfeiffer D D
Scientific reports 20190418 1
Automated diagnosis of tuberculosis (TB) from chest X-Rays (CXR) has been tackled with either hand-crafted algorithms or machine learning approaches such as support vector machines (SVMs) and convolutional neural networks (CNNs). Most deep neural network applied to the task of tuberculosis diagnosis have been adapted from natural image classification. These models have a large number of parameters as well as high hardware requirements, which makes them prone to overfitting and harder to deploy i ...[more]
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