Cargando…
Automated abnormality classification of chest radiographs using deep convolutional neural networks
As one of the most ubiquitous diagnostic imaging tests in medical practice, chest radiography requires timely reporting of potential findings and diagnosis of diseases in the images. Automated, fast, and reliable detection of diseases based on chest radiography is a critical step in radiology workfl...
Autores principales: | Tang, Yu-Xing, Tang, You-Bao, Peng, Yifan, Yan, Ke, Bagheri, Mohammadhadi, Redd, Bernadette A., Brandon, Catherine J., Lu, Zhiyong, Han, Mei, Xiao, Jing, Summers, Ronald M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7224391/ https://www.ncbi.nlm.nih.gov/pubmed/32435698 http://dx.doi.org/10.1038/s41746-020-0273-z |
Ejemplares similares
-
NegBio: a high-performance tool for negation and uncertainty detection in radiology reports
por: Peng, Yifan, et al.
Publicado: (2018) -
Convolutional Neural Networks (CNNs) for Pneumonia Classification on Pediatric Chest Radiographs
por: Saboo, Yash S, et al.
Publicado: (2023) -
Detection and visualization of abnormality in chest radiographs using modality-specific convolutional neural network ensembles
por: Rajaraman, Sivaramakrishnan, et al.
Publicado: (2020) -
Reproducibility of abnormality detection on chest radiographs using convolutional neural network in paired radiographs obtained within a short-term interval
por: Cho, Yongwon, et al.
Publicado: (2020) -
1992. Automated Classification of Pulmonary Tuberculosis-Associated Radiograph in the US Hospital-Scale Chest X-ray Database by Using Deep Convolutional Neural Network
por: Pongpirul, Krit, et al.
Publicado: (2018)