Cargando…
Improving the performance of CNN to predict the likelihood of COVID-19 using chest X-ray images with preprocessing algorithms
OBJECTIVE: This study aims to develop and test a new computer-aided diagnosis (CAD) scheme of chest X-ray images to detect coronavirus (COVID-19) infected pneumonia. METHOD: CAD scheme first applies two image preprocessing steps to remove the majority of diaphragm regions, process the original image...
Autores principales: | Heidari, Morteza, Mirniaharikandehei, Seyedehnafiseh, Khuzani, Abolfazl Zargari, Danala, Gopichandh, Qiu, Yuchen, Zheng, Bin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7510591/ https://www.ncbi.nlm.nih.gov/pubmed/32992136 http://dx.doi.org/10.1016/j.ijmedinf.2020.104284 |
Ejemplares similares
-
Developing global image feature analysis models to predict cancer risk and prognosis
por: Zheng, Bin, et al.
Publicado: (2019) -
COVID-Classifier: An automated machine learning model to assist in the diagnosis of COVID-19 infection in chest x-ray images
por: Khuzani, Abolfazl Zargari, et al.
Publicado: (2020) -
COVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images
por: Zargari Khuzani, Abolfazl, et al.
Publicado: (2021) -
Developing a Quantitative Ultrasound Image Feature Analysis Scheme to Assess Tumor Treatment Efficacy Using a Mouse Model
por: Mirniaharikandehei, Seyedehnafiseh, et al.
Publicado: (2019) -
A Comparison of Computer-Aided Diagnosis Schemes Optimized Using Radiomics and Deep Transfer Learning Methods
por: Danala, Gopichandh, et al.
Publicado: (2022)