Cargando…
3D CNN classification model for accurate diagnosis of coronavirus disease 2019 using computed tomography images
Purpose: The coronavirus disease (COVID-19) has been spreading rapidly around the world. As of August 25, 2020, 23.719 million people have been infected in many countries. The cumulative death toll exceeds 812,000. Early detection of COVID-19 is essential to provide patients with appropriate medical...
Autores principales: | Li, Yifan, Pei, Xuan, Guo, Yandong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Society of Photo-Optical Instrumentation Engineers
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8304701/ https://www.ncbi.nlm.nih.gov/pubmed/34322573 http://dx.doi.org/10.1117/1.JMI.8.S1.017502 |
Ejemplares similares
-
Fast whole-slide cartography in colon cancer histology using superpixels and CNN classification
por: Wilm, Frauke, et al.
Publicado: (2022) -
Video compression to support the expansion of whole-slide imaging into cytology
por: Zarella, Mark D., et al.
Publicado: (2019) -
Automatic extraction of cell nuclei from H&E-stained histopathological images
por: Yi, Faliu, et al.
Publicado: (2017) -
Detection of COVID-19 from chest x-ray images using transfer learning
por: Manokaran, Jenita, et al.
Publicado: (2021) -
Recurrence analysis on prostate cancer patients with Gleason score 7 using integrated histopathology whole-slide images and genomic data through deep neural networks
por: Ren, Jian, et al.
Publicado: (2018)