In modern society, spinal diseases that affect the spinal column, the spinal cord, and spinal nerves are becoming increasingly common, due to a reduction in physical labor and increasingly sedentary lifestyles. Much research has been devoted to human spine imaging and diagnosis because of a very large number of lesions in the spinal system, from purely skeletal disorders to primary nervous system disorders.

A variety of medical imaging modalities have played an important role in the diagnosis and treatment of spinal diseases. However, current diagnosis and treatment mainly depend on the clinical experience of physicians, which not only brings a heavy burden to doctors but also is inefficient or even inaccurate. In recent times, medical imaging data is growing increasingly rapidly, leading to a significant demand for efficient and accurate analysis. Artificial intelligence (AI) based techniques are increasingly needed to uncover hidden insights in clinical decision-making, connect patients with resources for self-management, and extract meaningful information from previously inaccessible, unstructured data assets.

The objective of this Special Issue is to provide a forum across AI and medical imaging research to advance the development of algorithms, models, and systems for imaging and analyzing spinal diseases. The scope of this Special Issue includes topics related to mathematics, AI technology, and methods of data science in advanced human spine imaging, modeling, and subsequent analysis. Submissions with significant theoretical, modeling, simulation, or experimental advances are encouraged. We welcome both original research and review articles.

Potential topics include but are not limited to the following:

• Advanced imaging and modeling techniques for human spines
• Computer-aided diagnosis in spinal images
• Image analysis, such as segmentation and registration, using spinal images
• Image processing in spinal medical imaging
• Machine learning and deep learning based spinal diseases classification and computation
• Multi-dimensional and multi-modality spine imaging and modeling
• AI-guided spine surgery and treatment
• Development of spinal imaging systems using AI and data science
• Spine rehabilitation with robot and AI technology and mathematical or statistical modeling
• Other applications based on modern mathematical and computational theory and techniques for human spine imaging, modeling, and treatment