Novel coronavirus (COVID-19) diagnosis using computer vision and artificial intelligence techniques: a review

被引:0
|
作者
Anuja Bhargava
Atul Bansal
机构
[1] GLA University,
来源
Multimedia Tools and Applications | 2021年 / 80卷
关键词
Computer vision; Computed tomography; Machine learning; Coronavirus; COVID-19;
D O I
暂无
中图分类号
学科分类号
摘要
The universal transmission of pandemic COVID-19 (Coronavirus) causes an immediate need to commit in the fight across the whole human population. The emergencies for human health care are limited for this abrupt outbreak and abandoned environment. In this situation, inventive automation like computer vision (machine learning, deep learning, artificial intelligence), medical imaging (computed tomography, X-Ray) has developed an encouraging solution against COVID-19. In recent months, different techniques using image processing are done by various researchers. In this paper, a major review on image acquisition, segmentation, diagnosis, avoidance, and management are presented. An analytical comparison of the various proposed algorithm by researchers for coronavirus has been carried out. Also, challenges and motivation for research in the future to deal with coronavirus are indicated. The clinical impact and use of computer vision and deep learning were discussed and we hope that dermatologists may have better understanding of these areas from the study.
引用
收藏
页码:19931 / 19946
页数:15
相关论文
共 50 条
  • [1] Novel coronavirus (COVID-19) diagnosis using computer vision and artificial intelligence techniques: a review
    Bhargava, Anuja
    Bansal, Atul
    MULTIMEDIA TOOLS AND APPLICATIONS, 2021, 80 (13) : 19931 - 19946
  • [2] A Review on Deep Learning Techniques for the Diagnosis of Novel Coronavirus (COVID-19)
    Islam, Md. Milon
    Karray, Fakhri
    Alhajj, Reda
    Zeng, Jia
    IEEE ACCESS, 2021, 9 : 30551 - 30572
  • [3] Smart and Automated Diagnosis of COVID-19 Using Artificial Intelligence Techniques
    Alajmi, Masoud
    Elshakankiry, Osama A.
    El-Shafai, Walid
    El-Sayed, Hala S.
    Sallam, Ahmed, I
    El-Hoseny, Heba M.
    Sedik, Ahmed
    Faragallah, Osama S.
    INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2022, 32 (03): : 1403 - 1413
  • [4] Accelerated Diagnosis of Novel Coronavirus (COVID-19)-Computer Vision with Convolutional Neural Networks (CNNs)
    Ghani, Arfan
    Aina, Akinyemi
    See, Chan Hwang
    Yu, Hongnian
    Keates, Simeon
    ELECTRONICS, 2022, 11 (07)
  • [5] Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation, and Diagnosis for COVID-19
    Shi, Feng
    Wang, Jun
    Shi, Jun
    Wu, Ziyan
    Wang, Qian
    Tang, Zhenyu
    He, Kelei
    Shi, Yinghuan
    Shen, Dinggang
    IEEE REVIEWS IN BIOMEDICAL ENGINEERING, 2021, 14 : 4 - 15
  • [6] Artificial Intelligence Models and Techniques Applied to COVID-19: A Review
    Munoz, Lilia
    Villarreal, Vladimir
    Nielsen, Mel
    Caballero, Yen
    Sitton-Candanedo, Ines
    Corchado, Juan M.
    ELECTRONICS, 2021, 10 (23)
  • [7] Smart Artificial Intelligence techniques using embedded band for diagnosis and combating COVID-19
    Ashwin, M.
    Alqahtani, Abdulrahman Saad
    Mubarakali, Azath
    MICROPROCESSORS AND MICROSYSTEMS, 2023, 98
  • [8] COVID-19 diagnosis from routine blood tests using artificial intelligence techniques
    Rikan, Samin Babaei
    Azar, Amir Sorayaie
    Ghafari, Ali
    Mohasefi, Jamshid Bagherzadeh
    Pirnejad, Habibollah
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2022, 72
  • [9] Role of artificial intelligence in the diagnosis of COVID-19: A mini review
    Mohammed, P. K.
    Gulati, Saakshi
    Gupta, Shivangi
    JOURNAL OF ACUTE DISEASE, 2022, 11 (05) : 168 - 172
  • [10] Artificial intelligence in pulmonary medicine: computer vision, predictive model and COVID-19
    Khemasuwan, Danai
    Sorensen, Jeffrey S.
    Colt, Henri G.
    EUROPEAN RESPIRATORY REVIEW, 2020, 29 (157): : 1 - 16