AI in Imaging
A section of Journal of Imaging (ISSN 2313-433X).
Section Information
Aims
Imaging science is a multidisciplinary field concerned with the generation, collection, duplication, analysis, modification, and visualization of images. As an evolving field, it includes research and researchers from the fields of physics, mathematics, electrical engineering, computer vision, computer science, and perceptual psychology. On the other hand, artificial intelligence (AI) is intelligence demonstrated by computers, as opposed to human or animal intelligence. Intelligence encompasses the ability to learn and to reason, to generalize, and to infer meaning. Machine learning, deep learning, and neural networks, all sub-fields of AI, focus on the use of data and algorithms to imitate the way that humans learn, gradually improving the accuracy of the problems posed, in particular those related to imaging applications.
Scope
The Section “AI in Imaging” welcomes papers showing the most recent approaches related to AI in imaging. Both basic and applied research is appreciated in the following non-exhaustive list of topics:
- AI in augmented imaging systems, devices and equipment;
- AI in original imaging methods and modalities;
- AI in enhanced imaging techniques and technologies;
- AI in advanced imaging studies and tests;
- AI in novel imaging software and systems;
- AI in unconventional direct and digital imaging;
- AI in groundbreaking medical and/or diagnostic imaging, including, but not limited to:
- brain imaging;
- calcium imaging;
- fluorescence imaging;
- functional imaging;
- infrared imaging;
- molecular imaging;
- resonance imaging;
- ultrasound imaging.
- Innovative applications of AI in imaging and quality control;
- AI-based image synthesis and analysis.
Editorial Board
Topical Advisory Panel
Special Issues
Following special issues within this section are currently open for submissions:
- Industrial Machine Learning with Image Technology Integration (Deadline: 28 February 2025)
- Explainable AI in Computer Vision (Deadline: 30 April 2025)
