On-line 4D Cone Beam CT Reconstruction for Real-time Tumor Localization
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Solution Overview
Problem
Current cone beam CT reconstruction methods require offline analysis, which is not suitable for real-time image guidance during treatments, especially for hypofractionated lung radiotherapy, where large motion artifacts lead to poor 3D image quality.
Innovation Solution
An in-line 4D cone beam CT reconstruction algorithm that processes images in parallel with acquisition, using a system with a rotating source and detector, image storage, and processing means to condense, analyze, and backproject images in real-time, allowing for phase determination and image allocation during treatment, enabling rapid 4D reconstruction and tumor localization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If offline analysis is used for cone beam CT reconstruction, then image quality can be improved through comprehensive processing, but real-time image guidance capability is lost
Solution Approach 1:
The patent segments the reconstruction process into multiple independent stages: data acquisition, preliminary processing, iterative reconstruction, and post-processing. Each stage can be processed independently and in parallel, enabling real-time computation while maintaining comprehensive image quality through complete processing of all stages.
Solution Approach 2:
The system performs preliminary processing of projection data immediately during acquisition, including normalization, logarithmic transformation, and motion estimation. This preliminary action prepares the data for rapid iterative reconstruction without waiting for complete data collection, enabling real-time guidance while maintaining final image quality.
2Measurement precision
If comprehensive image processing is performed to eliminate motion artifacts, then image quality improves, but processing time increases
Solution Approach 1:
The patent implements continuous iterative reconstruction where each iteration builds upon the previous one, with motion estimation and correction applied continuously throughout the reconstruction process. This continuous action allows the system to produce progressively improving images in real-time rather than requiring complete processing before any output.
Solution Approach 2:
The system dynamically adjusts the number of iterations and processing parameters based on the specific clinical situation and motion characteristics. For small motions, fewer iterations are needed, maintaining high processing speed. For large motions, the system automatically increases iterations to eliminate artifacts, optimizing the balance between speed and quality for each case.
3Manufacturing precision
If motion estimation is performed accurately to correct respiratory artifacts, then reconstruction accuracy improves, but computational complexity increases
Solution Approach 1:
The patent replaces complex mechanical motion tracking systems with computational motion estimation performed directly on the projection images. Algorithms automatically detect diaphragm position and tumor motion from the image data itself, eliminating the need for external tracking devices while achieving accurate motion correction through image processing alone.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables on-line verification and correction of tumor position during treatment, providing accurate 3D images free from respiratory artifacts, with 4D reconstructions available within seconds of scanning, facilitating efficient hypofractionated radiotherapy without implanted markers.
Implementation Method 1
a source of penetrating radiation and a two-dimensional detector for the radiation... The penetrating radiation is suitably x-radiation
Data Source
AI summary
An in-line 4D cone beam CT reconstruction algorithm queues a limited number of projection images such that the phase determination algorithm can look-ahead. At regular intervals, the queue is scanned and those images which have enough look-ahead to obtain phase information are filtered and back-projected. The algorithm thus keeps up with the image acquisition speed and produces a 4D reconstruction within a few seconds of the end of scanning.