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文献清单:“医学影像与计算机视觉应用”方向| MDPI Journal of Imaging |
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期刊名:Journal of Imaging
期刊主页:https://www.mdpi.com/journal/jimaging
还在为筛选文献而发愁?别急,这份“医学影像与计算机视觉应用”方向的文献清单,也许能为你提供灵感!
1.
A Survey on Explainable Artificial Intelligence (XAI) Techniques for Visualizing Deep Learning Models in Medical Imaging
关于医学影像中深度学习模型可视化的可解释人工智能(XAI)技术综述
https://www.mdpi.com/2313-433X/10/10/239
Bhati, D.; Neha, F.; Amiruzzaman, M. A Survey on Explainable Artificial Intelligence (XAI) Techniques for Visualizing Deep Learning Models in Medical Imaging. J. Imaging 2024, 10, 239. https://doi.org/10.3390/jimaging10100239
2.
Deep Learning for Pneumonia Detection in Chest X-ray Images: A Comprehensive Survey
基于深度学习的胸部X光图像肺炎检测研究:综述
https://www.mdpi.com/2313-433X/10/8/176
Siddiqi, R.; Javaid, S. Deep Learning for Pneumonia Detection in Chest X-ray Images: A Comprehensive Survey. J. Imaging 2024, 10, 176. https://doi.org/10.3390/jimaging10080176
3.
Advancements and Challenges in Handwritten Text Recognition: A Comprehensive Survey
手写文本识别的研究进展与挑战:综述
https://www.mdpi.com/2313-433X/10/1/18
AlKendi, W.; Gechter, F.; Heyberger, L.; Guyeux, C. Advancements and Challenges in Handwritten Text Recognition: A Comprehensive Survey. J. Imaging 2024, 10, 18. https://doi.org/10.3390/jimaging10010018
4.
A CNN Hyperparameters Optimization Based on Particle Swarm Optimization for Mammography Breast Cancer Classification
基于粒子群优化的CNN超参数调优在乳腺X线摄影乳腺癌分类中的应用
https://www.mdpi.com/2313-433X/10/2/30
Aguerchi, K.; Jabrane, Y.; Habba, M.; El Hassani, A.H. A CNN Hyperparameters Optimization Based on Particle Swarm Optimization for Mammography Breast Cancer Classification. J. Imaging 2024, 10, 30. https://doi.org/10.3390/jimaging10020030
5.
Applied artificial intelligence in healthcare: A review of computer vision technology application in hospital settings.
人工智能在医疗保健中的应用:计算机视觉技术在医院场景下的应用综述
https://www.mdpi.com/2313-433X/10/4/81
Lindroth, H.; Nalaie, K.; Raghu, R.; Ayala, I.N.; Busch, C.; Bhattacharyya, A.; Moreno Franco, P.; Diedrich, D.A.; Pickering, B.W.; Herasevich, V. Applied Artificial Intelligence in Healthcare: A Review of Computer Vision Technology Application in Hospital Settings. J. Imaging 2024, 10, 81. https://doi.org/10.3390/jimaging10040081
6.
Enhanced Self-Checkout System for Retail Based on Improved YOLOv10
基于改进型YOLOv10的增强型零售自助结账系统
https://www.mdpi.com/2313-433X/10/10/248
Tan, L.; Liu, S.; Gao, J.; Liu, X.; Chu, L.; Jiang, H. Enhanced Self-Checkout System for Retail Based on Improved YOLOv10. J. Imaging 2024, 10, 248. https://doi.org/10.3390/jimaging10100248
7.
Image analysis in pathology and cytopathology: from early days to current perspectives
病理学及细胞病理学图像分析:发展历程与当前研究视角
https://www.mdpi.com/2313-433X/10/10/252
Mezei, T.; Kolcsár, M.; Joó, A.; Gurzu, S. Image Analysis in Histopathology and Cytopathology: From Early Days to Current Perspectives. J. Imaging 2024, 10, 252. https://doi.org/10.3390/jimaging10100252
8.
Explainable AI-based Skin Cancer Detection using CNN, Par-ticle Swarm Optimization and Machine Learning
基于可解释人工智能的卷积神经网络及粒子群优化联合机器学习在皮肤癌检测中的应用研究
https://www.mdpi.com/2313-433X/10/12/332
Shah, S.A.H.; Shah, S.T.H.; Khaled, R.; Buccoliero, A.; Shah, S.B.H.; Di Terlizzi, A.; Di Benedetto, G.; Deriu, M.A. Explainable AI-Based Skin Cancer Detection Using CNN, Particle Swarm Optimization and Machine Learning. J. Imaging 2024, 10, 332. https://doi.org/10.3390/jimaging10120332
9.
Optimizing Vision Transformers for Histopathology: Pretraining and Normalization in Breast Cancer Classification
面向组织病理学的视觉Transformer优化:乳腺癌分类中的预训练与归一化研究
https://www.mdpi.com/2313-433X/10/5/108
Baroni, G.L.; Rasotto, L.; Roitero, K.; Tulisso, A.; Di Loreto, C.; Della Mea, V. Optimizing Vision Transformers for Histopathology: Pretraining and Normalization in Breast Cancer Classification. J. Imaging 2024, 10, 108. https://doi.org/10.3390/jimaging10050108
10.
Review of Image-Processing-Based Technology for Structural Health Monitoring of Civil Infrastructures
基于图像处理技术的土木基础设施结构健康监测研究综述
https://www.mdpi.com/2313-433X/10/4/93
Kim, J.-W.; Choi, H.-W.; Kim, S.-K.; Na, W.S. Review of Image-Processing-Based Technology for Structural Health Monitoring of Civil Infrastructures. J. Imaging 2024, 10, 93. https://doi.org/10.3390/jimaging10040093
11.
Current Status and Challenges and Future Trends of Deep Learning-Based Intrusion Detection Models
基于深度学习的入侵检测:现状、挑战与未来趋势
https://www.mdpi.com/2313-433X/10/10/254
Wu, Y.; Zou, B.; Cao, Y. Current Status and Challenges and Future Trends of Deep Learning-Based Intrusion Detection Models. J. Imaging 2024, 10, 254. https://doi.org/10.3390/jimaging10100254
12.
Residual-Based Multi-Stage Deep Learning Framework for Computer-Aided Alzheimer’s Disease Detection
基于残差的多阶段深度学习框架用于计算机辅助阿尔茨海默症检测
https://www.mdpi.com/2313-433X/10/6/141
Hassan, N.; Musa Miah, A.S.; Shin, J. Residual-Based Multi-Stage Deep Learning Framework for Computer-Aided Alzheimer’s Disease Detection. J. Imaging 2024, 10, 141. https://doi.org/10.3390/jimaging10060141
13.
Video-Based Sign Language Recognition via ResNet and LSTM Network
基于视频的ResNet与LSTM网络手语识别方法研究
https://www.mdpi.com/2313-433X/10/6/149
Huang, J.; Chouvatut, V. Video-Based Sign Language Recognition via ResNet and LSTM Network. J. Imaging 2024, 10, 149. https://doi.org/10.3390/jimaging10060149
14.
Image Inpainting Forgery Detection: A Review
图像修复篡改检测技术综述
https://www.mdpi.com/2313-433X/10/2/42
Barglazan, A.-A.; Brad, R.; Constantinescu, C. Image Inpainting Forgery Detection: A Review. J. Imaging 2024, 10, 42. https://doi.org/10.3390/jimaging10020042
15.
Revolutionizing Cow Welfare Monitoring: A Novel Top-View Perspective with Depth Camera-Based Lameness Classification
基于深度摄像头俯视视角的奶牛跛行分类新方法及其对福利监测的革新
https://www.mdpi.com/2313-433X/10/3/67
Tun, S.C.; Onizuka, T.; Tin, P.; Aikawa, M.; Kobayashi, I.; Zin, T.T. Revolutionizing Cow Welfare Monitoring: A Novel Top-View Perspective with Depth Camera-Based Lameness Classification. J. Imaging 2024, 10, 67. https://doi.org/10.3390/jimaging10030067
期刊介绍
主编:Professor Raimondo Schettini
Department of Informatics, Systems and Communication, University of Milano-Bicocca, viale Sarca, 336, 20126 Milano, Italy
是一个国际性的、多学科/跨学科的、开放获取的、同行评审的期刊,发表影像学研究各个领域的综述、原创研究论文、和通讯文章等。期刊目标是为图像采集、处理和理解等成像领域的研究提供一个高级论坛。期刊已被 Scopus、ESCI(Web of Science)、PubMed、PMC、 dblp、Inspec、Ei Compendex等数据库收录。
2025 Impact Factor: 3.8
2025 CiteScore: 7.3
Time to First Decision: 21.3 days
Acceptance to Publication: 3.6 days
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