Medical images classification using deep learning: a survey

被引：0
作者：
Rakesh Kumar
Pooja Kumbharkar
Sandeep Vanam
Sanjeev Sharma
机构：
[1] Indian Institute of Information Technology Pune,
来源：
Multimedia Tools and Applications | 2024年 / 83卷
关键词：
Image classification; Deep Learning models; Performance; Features; Medical imaging;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Deep learning has made significant advancements in recent years. The technology is rapidly evolving and has been used in numerous automated applications with minimal loss. With these deep learning methods, medical image analysis for disease detection can be performed with minimal errors and losses. A survey of deep learning-based medical image classification is presented in this paper. As a result of their automatic feature representations, these methods have high accuracy and precision. This paper reviews various models like CNN, Transfer learning, Long short term memory, Generative adversarial networks, and Autoencoders and their combinations for various purposes in medical image classification. The total number of papers reviewed is 158. In the study, we discussed the advantages and limitations of the methods. A discussion is provided on the various applications of medical imaging, the available datasets for medical imaging, and the evaluation metrics. We also discuss the future trends in medical imaging using artificial intelligence.
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收藏
页码：19683 / 19728
页数：45
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  • [1] Abadeh MS(2020)Brain MRI analysis using a deep learning based evolutionary approach Neural Netw 126 218-234
  • [2] Shahamat H(2023)Deep transfer learning based parkinson’s disease detection using optimized feature selection IEEE Access 11 3511-3524
  • [3] Abdullah SM(2022)An Automated Image Segmentation and Useful Feature Extraction Algorithm for Retinal Blood Vessels in Fundus Images Electronics 11 1295-22825
  • [4] Abdulsahib A(2020)Uncertainty assisted robust tuberculosis identification with bayesian convolutional neural networks IEEE Access 8 22812-52587
  • [5] Mahmoud M(2020)A novel approach to improving brain image classification using mutual information-accelerated singular value decomposition IEEE Access 8 52575-64288
  • [6] Abideen ZU(2019)A novel approach for multi-label chest x-ray classification of common thorax diseases IEEE Access 7 64279-17
  • [7] Ghafoor M(2016)Brain tumour classification using two-tier classifier with adaptive segmentation technique IET Comput Vis 10 9-105670
  • [8] Munir K(2021)COVID-19 detection in X-ray images using convolutional neural networks Mach Learn Appl 6 100138-5516
  • [9] Saqib M(2020)Deep convolution neural network for big data medical image classification IEEE Access 8 105659-66061
  • [10] Ullah A(2020)A survey of the recent architectures of deep convolutional neural networks Artif Intell Rev 53 5455-156
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