Special issue on 3D medical image processing and analysis

Medical images show different characteristics in accordance with the target organs and suspected abnormalities. The general 3D modalities used for medical imaging include Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI). Recently, we have witnessed a rapid increase in the use of deep learning models to process and analyze 3D medical imaging data. This is due to the great improvement in the efficiency and effectiveness of 3D Convolutional Neural Networks (CNNs) as compared to traditional hand-crafted methods.

This special issue will focus on state-of-the-art 3D techniques and their applications in medical image processing and analysis in healthcare. It will also explore developments that benefit the training of neural networks and effectively leverage different information sources in healthcare. In addition, it will aim to inspire the interpretability and ethics of AI, since they are the foundations of medical safety.

Topics of interest:

These include, but are not limited to:

• 3D medical imaging
• 3D medical printing
• 3D medical modelling
• AI and robotics in healthcare
• AI-equipped healthcare systems
• AI in maintaining health equity
• AI for good health
• Multi-modal fusion
• Data augmentation
• Image quality assessment
• Image enhancement
• Explainable AI in healthcare
• Ethics of AI in healthcare

Key dates:

• Submissions close: 30 December 2023
• First reviews due: 15 February 2024
• Revised manuscripts due: 15 March 2024
• Final decision: 30 April 2024

Submission instructions:

Please read the Guide for Authors before submitting. Submissions should be made via the online editorial system.

Guest Editors:

• Xiaohong Liu, Shanghai Jiao Tong University, Email: Xiaohongliu@sjtu.edu.cn
• Tao Tan, Macao Polytechnic University, Email: taotan@mpu.edu.mo
• Menghan Hu, East China Normal University, Email: mhhu@ce.ecnu.edu.cn