A novel open-source CADs platform for 3D CT pulmonary analysis

Area of Science:

• Medical Imaging
• Computer-Aided Diagnosis
• Oncology

Background:

• Pulmonary nodules are critical indicators for lung cancer.
• Early detection of lung nodules can significantly reduce mortality rates.
• Existing computer-aided diagnosis (CAD) systems require enhanced functionality and flexibility.

Purpose of the Study:

• To propose an efficient, open-source CAD platform for 3D CT pulmonary nodule analysis.
• To provide professional doctors with advanced tools for improved diagnostic services.
• To create a versatile platform supporting flexible equipment integration and user-friendly operation.

Main Methods:

• Developed a CAD platform with core functions: Basic Image Processing, Intelligent Image Analysis, Multi-View Image Visualization, Report Editing and Generation, User Information Management, and Inference Service Monitoring.
• Implemented a plugin architecture for seamless integration of state-of-the-art or user-defined algorithms.
• Conducted system evaluation through use-case testing.

Main Results:

• The proposed platform offers a comprehensive suite of tools for 3D CT pulmonary nodule analysis.
• The open-source nature and plugin architecture allow for high flexibility and extensibility.
• Use-case testing validated the platform's effectiveness and universality in clinical scenarios.

Conclusions:

• The developed CAD platform is effective and versatile for 3D CT pulmonary nodule analysis.
• The system supports enhanced early lung cancer detection through advanced diagnostic capabilities.
• The open-source platform provides a valuable tool for medical professionals, improving diagnostic services.