Cargando…
CXR-RefineDet: Single-Shot Refinement Neural Network for Chest X-Ray Radiograph Based on Multiple Lesions Detection
The workload of radiologists has dramatically increased in the context of the COVID-19 pandemic, causing misdiagnosis and missed diagnosis of diseases. The use of artificial intelligence technology can assist doctors in locating and identifying lesions in medical images. In order to improve the accu...
Autores principales: | Lin, Cong, Zheng, Yongbin, Xiao, Xiuchun, Lin, Jialun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8759881/ https://www.ncbi.nlm.nih.gov/pubmed/35035832 http://dx.doi.org/10.1155/2022/4182191 |
Ejemplares similares
-
Dense-RefineDet for Traffic Sign Detection and Classification
por: Sun, Chang, et al.
Publicado: (2020) -
A Robust Fabric Defect Detection Method Based on Improved RefineDet
por: Xie, Huosheng, et al.
Publicado: (2020) -
CXray-EffDet: Chest Disease Detection and Classification from X-ray Images Using the EfficientDet Model
por: Nawaz, Marriam, et al.
Publicado: (2023) -
VinDr-CXR: An open dataset of chest X-rays with radiologist’s annotations
por: Nguyen, Ha Q., et al.
Publicado: (2022) -
Learning from imbalanced COVID-19 chest X-ray (CXR) medical imaging data
por: Chan, Jonathan H., et al.
Publicado: (2022)