Tomographic Scanner Object Edge Detection and Data Segmentation
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Solution Overview
Problem
Tomographic systems face challenges in accurately determining the extent of objects within the scanning device, leading to confusion between external and internal measurements, and struggle to keep pace with data acquisition due to processing during gaps between objects, resulting in inefficient data collection and reconstruction.
Innovation Solution
A CT system that continuously acquires raw data and determines the leading and trailing edges of objects using detector signals, allowing for precise data recording and processing only during the object's presence, thereby segmenting the data stream effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the tomographic system uses external systems with passive curtains to determine object extent, then the system can identify objects externally, but objects may be repositioned inside the scanning device causing confusion between external and internal measurements
Solution Approach 1:
The patent introduces a light source and light sensor as intermediary devices positioned within the scanning device to detect object leading and trailing edges. This intermediary measurement system directly measures object extent at the scan location, eliminating the confusion between external curtain measurements and internal object positions by providing a direct observation of object boundaries within the scanning volume.
Solution Approach 2:
The patent replaces the mechanical passive curtain system with an optical detection system using light sources and light sensors. This substitution allows for more precise and reliable object extent measurement within the scanning device, as the optical system can detect object boundaries without physical contact or mechanical interaction that might cause repositioning.
2Productivity
If the tomographic system processes data during gaps between objects, then the reconstruction subsystem can catch up with data acquisition, but data collection becomes inefficient and computational time increases
Solution Approach 1:
The patent performs preliminary action by detecting object leading and trailing edges using light sources and sensors before the object fully enters the scanning volume. This allows the system to pre-identify object boundaries and prepare for data acquisition, ensuring that data is collected efficiently only when objects are present and eliminating unnecessary processing during gaps.
Solution Approach 2:
The patent implements continuous data acquisition throughout the object's passage through the scanning device, rather than waiting for gaps between objects to process data. The system continuously monitors for object presence using light detection and maintains continuous data collection, eliminating idle processing time and maximizing throughput by keeping the reconstruction subsystem continuously engaged with valid data.
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
This approach enables efficient data processing and image reconstruction only when objects are present, maximizing throughput and reducing computational time and cost by eliminating unnecessary data processing during gaps.
Implementation Method 1
an X-ray system including a detector, determining a leading edge and a trailing edge of a first object of the stream of objects from the raw data acquired by the detector
Data Source
AI summary
A method for scanning a stream of objects includes continuously acquiring raw data of the stream of objects using an X-ray system including a detector, determining a leading edge and a trailing edge of a first object of the stream of objects from the raw data acquired by the detector using a control system, processing acquired raw data of the first object based on the determined leading edge and the determined trailing edge using the control system, and reconstructing an image of the first object using at least the processed raw data. A system configured to perform the method is also disclosed.