Advanced Computer Vision and Data Fusion Techniques for Medical Imaging Analysis and Processing
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: closed (20 April 2025) | Viewed by 967
Special Issue Editor
Interests: computer vision; artificial intelligence; machine learning; deep learning; medical image analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In today's digital age, medical imaging has become an essential tool in diagnostics, treatment planning, and healthcare. Integrating advanced computer vision techniques with data fusion and machine learning transforms how medical images are analyzed and processed, enabling precise and automated healthcare. The vast and complex data from 2D and 3D scans and multimodal imaging requires more advanced methods than traditional approaches, which are no longer sufficient to meet the growing demands of accuracy, speed, and personalization in medical care. This Special Issue explores innovative advances in computer vision for medical image analysis, focusing on techniques like deep learning, data mining, and 3D imaging reconstruction that can extract key insights. Significant areas include explainable and trustworthy AI, early disease detection, and predictive modelling, ensuring systems are reliable in healthcare environments.
Additionally, this issue will delve into the application of data fusion techniques to integrate diverse datasets, improving diagnostic accuracy and personalizing treatment plans. Advanced 3D reconstruction, feature extraction, and motion analysis will be explored, with applications in image-guided surgery and interventions where precision is essential.
The topics of interest for this Special Issue include but are not limited to the following:
- Deep-learning-driven medical image analysis;
- AI-augmented computer-aided diagnosis (CAD) systems;
- Imaging biomarkers and disease pattern recognition;
- Multimodal medical data fusion and integration;
- Interpretable and trustworthy AI models for medical imaging;
- Predictive screening and early disease detection algorithms;
- Advanced feature extraction and automated image segmentation;
- Three-dimensional image reconstruction and volumetric analysis;
- Big data mining and predictive modelling for medical imaging;
- Real-time image-guided surgery and minimally invasive interventions;
- Geometric shape and motion analysis in medical imaging;
- Remote diagnostics through telemedicine and image processing;
- Immersive virtual and augmented reality for medical imaging guidance.
Dr. Imran Ahmed
Guest Editor
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Keywords
- computer vision
- medical image analysis
- data fusion techniques
- machine learning
- deep learning
- data mining
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