Cargando…
1992. Automated Classification of Pulmonary Tuberculosis-Associated Radiograph in the US Hospital-Scale Chest X-ray Database by Using Deep Convolutional Neural Network
BACKGROUND: Automated classification of chest radiograph (CXR) using deep convolutional neural network (DCCN) has emerged as an attractive option for tuberculosis surveillance and detection. The National Institute of Health (NIH) ChestX-ray8 database comprises 32,717 patients with X-ray images that...
Autores principales: | Pongpirul, Krit, Sathitratanacheewin, Seelwan, Sunanta, Panasun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6254316/ http://dx.doi.org/10.1093/ofid/ofy210.1648 |
Ejemplares similares
-
Deep learning for automated classification of tuberculosis-related chest X-Ray: dataset distribution shift limits diagnostic performance generalizability
por: Sathitratanacheewin, Seelwan, et al.
Publicado: (2020) -
Automated abnormality classification of chest radiographs using deep convolutional neural networks
por: Tang, Yu-Xing, et al.
Publicado: (2020) -
Convolutional Neural Networks (CNNs) for Pneumonia Classification on Pediatric Chest Radiographs
por: Saboo, Yash S, et al.
Publicado: (2023) -
Convolutional neural networks for the classification of chest X-rays in the IoT era
por: Almezhghwi, Khaled, et al.
Publicado: (2021) -
Effective Utilization of Multiple Convolutional Neural Networks for Chest X-Ray Classification
por: Rammuni Silva, Ravidu Suien, et al.
Publicado: (2022)