Cargando…
Review and classification of AI-enabled COVID-19 CT imaging models based on computer vision tasks
This article presents a systematic overview of artificial intelligence (AI) and computer vision strategies for diagnosing the coronavirus disease of 2019 (COVID-19) using computerized tomography (CT) medical images. We analyzed the previous review works and found that all of them ignored classifying...
Autores principales: | Hassan, Haseeb, Ren, Zhaoyu, Zhao, Huishi, Huang, Shoujin, Li, Dan, Xiang, Shaohua, Kang, Yan, Chen, Sifan, Huang, Bingding |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8684223/ https://www.ncbi.nlm.nih.gov/pubmed/34953356 http://dx.doi.org/10.1016/j.compbiomed.2021.105123 |
Ejemplares similares
-
Supervised and weakly supervised deep learning models for COVID-19 CT diagnosis: A systematic review
por: Hassan, Haseeb, et al.
Publicado: (2022) -
Deep Learning Applications in Computed Tomography Images for Pulmonary Nodule Detection and Diagnosis: A Review
por: Li, Rui, et al.
Publicado: (2022) -
Deep Segmentation Networks for Segmenting Kidneys and Detecting Kidney Stones in Unenhanced Abdominal CT Images
por: Li, Dan, et al.
Publicado: (2022) -
A Robust Brain Tumor Detector Using BiLSTM and Mayfly Optimization and Multi-Level Thresholding
por: Mahum, Rabbia, et al.
Publicado: (2023) -
AI-enabled radiologist in the loop: novel AI-based framework to augment radiologist performance for COVID-19 chest CT medical image annotation and classification from pneumonia
por: Ghayvat, Hemant, et al.
Publicado: (2022)