来源：Journal of Imaging 发布时间：2026/9/1 16:26:00

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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

期刊名：Journal of Imaging

期刊主页：https://www.mdpi.com/journal/jimaging

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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. Imaging2024,10, 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. Imaging2024,10, 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. Imaging2024,10, 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. Imaging2024,10, 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. Imaging2024,10, 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. Imaging2024,10, 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. Imaging2024,10, 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. Imaging2024,10, 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. Imaging2024,10, 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. Imaging2024,10, 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. Imaging2024,10,254.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. Imaging2024,10, 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. Imaging2024,10, 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. Imaging2024,10, 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. Imaging2024,10, 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