Review of CT image reconstruction open source toolkits.

Area of Science:

• Medical Imaging
• Computer Vision
• Scientific Computing

Background:

• Computed tomography (CT) is vital across medical, industrial, and security fields.
• Image reconstruction is a fundamental technology in CT imaging.
• Open-source toolkits are crucial for advancing CT research.

Purpose of the Study:

• To systematically review publicly available CT image reconstruction open-source toolkits.
• To categorize toolkits based on environment, object models, imaging geometries, and algorithms.
• To include deep learning-based reconstruction methods alongside traditional algorithms.

Main Methods:

• Systematic literature review of CT image reconstruction open-source software.
• Categorization of toolkits by technical specifications and algorithmic approaches.
• Inclusion of analytic, iterative, and deep learning-based reconstruction algorithms.

Main Results:

• Identified and categorized various open-source CT reconstruction toolkits.
• Detailed the environments, object models, and imaging geometries of reviewed software.
• Highlighted the integration of deep learning networks as a modern reconstruction category.

Conclusions:

• A comprehensive summary of available CT reconstruction software is presented.
• This review facilitates the selection and utilization of appropriate toolkits for CT research.
• The findings will accelerate innovation in CT image reconstruction technologies.