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Automatic seed picking for brachytherapy postimplant validation with 3D CT images.
Guobin Zhang1,2,3, Qiyuan Sun1,2, Shan Jiang4,5
1Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronical System, Tianjin, 300384, China.
Summary
An automatic method accurately identifies brachytherapy seed location and orientation in 3D CT images. This approach enhances postimplant validation accuracy for improved radiotherapy quality assurance.
Area of Science:
- Medical Physics
- Image Processing
- Radiotherapy Technology
Background:
- Postimplant validation is crucial for brachytherapy quality assurance.
- Accurate identification of implanted seeds is essential for reliable validation.
- Current methods may lack the precision required for optimal feedback.
Purpose of the Study:
- To develop an automatic approach for picking implanted brachytherapy seeds in 3D CT images.
- To efficiently determine seed configuration, including location and orientation.
- To enhance the accuracy of postimplant validation in brachytherapy.
Main Methods:
- Seed segmentation from CT images using histogram-based thresholding.
- Classification of touching and single seeds with filtering and denoising.
- Separation of touching seeds via Canny edge detection and concave point matching.
- Determination of seed configuration using image moment computation.
Main Results:
- The automated method demonstrated promising results in phantom and patient data.
- Seed location error was within 0.8 mm, and orientation error within 3.5 degrees.
- Average processing time for seed picking was 8.7 seconds per 100 seeds.
Conclusions:
- An automatic, efficient, and robust approach for determining brachytherapy seed location and orientation in 3D CT images was proposed.
- The method successfully exhibited good performance in both phantom and patient data experiments.
- This technique can significantly improve the quality assurance process in brachytherapy.
