Detecting Tuberculosis-Consistent Findings in Lateral Chest X-Rays Using an Ensemble of CNNs and Vision Transformers

Detecting Tuberculosis-Consistent Findings in Lateral Chest X-Rays Using an Ensemble of CNNs and Vision Transformers

Research on detecting Tuberculosis (TB) findings on chest radiographs (or Chest X-rays: CXR) using convolutional neural networks (CNNs) has demonstrated superior performance due to the emergence of publicly available, large-scale datasets with expert annotations and availability of scalable computat...

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Bibliographic Details
Main Authors: Sivaramakrishnan Rajaraman, Ghada Zamzmi, Les R. Folio, Sameer Antani
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-02-01
Series:Frontiers in Genetics
Subjects:
chest radiographs
CNN
deep learning
tuberculosis classification and localization
vision transformers
ensemble learning
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2022.864724/full

Internet

https://www.frontiersin.org/articles/10.3389/fgene.2022.864724/full

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