Tomographic Reconstruction Using Combined Circle and Line Trajectories

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Solution Overview

Problem

Conventional CT reconstruction algorithms face challenges in achieving high-quality images due to cone beam artifacts and inefficiencies, particularly when using circular trajectories, which result in incomplete data coverage and require significant processing resources.

Innovation Solution

A method combining circle and line scan data using ramp filters for circle data reconstruction and Hilbert filters for line data reconstruction, allowing for the removal of cone beam artifacts and improving image quality without requiring extensive hardware modifications.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If conventional FDK algorithm is used for circular trajectory reconstruction, then computational efficiency is improved, but cone beam artifacts occur due to incomplete data coverage

Engineering Contradiction:

Improvecomputational efficiencyVSAvoidimage quality

Core Design Contradiction:

ProductivityVSManufacturing precision

Solution Approach 1:

The patent combines circular trajectory data and linear trajectory data into a unified reconstruction framework. The circular trajectory provides high computational efficiency while the linear trajectory supplements incomplete data coverage, eliminating cone beam artifacts through merged data reconstruction

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The reconstruction process is segmented into two distinct parts: circular trajectory reconstruction using FDK algorithm for efficiency, and linear trajectory reconstruction for artifact correction. Each trajectory type is processed separately and then integrated to produce the final artifact-free image

Inventive Principle:

Principle #1Segmentation

2Manufacturing precision

If exact reconstruction algorithms are used to eliminate cone beam artifacts, then image quality is improved, but processing time and computational resources increase significantly

Engineering Contradiction:

Improveimage qualityVSAvoidprocessing time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

Instead of using computationally intensive exact reconstruction algorithms for the entire dataset, the patent applies partial correction by using linear trajectory data only to supplement and correct specific regions affected by cone beam artifacts, maintaining fast processing while improving image quality

Inventive Principle:

Principle #16Partial or excessive action

3Speed

If circular trajectory scan is used, then scan speed is improved, but data coverage completeness deteriorates

Engineering Contradiction:

Improvescan speedVSAvoiddata coverage completeness

Core Design Contradiction:

SpeedVSLoss of information

Solution Approach 1:

The patent merges circular trajectory scanning (fast but incomplete coverage) with linear trajectory scanning (slower but complete coverage). The circular scan maintains speed advantage while the linear scan fills in missing data regions, achieving both speed and completeness

Inventive Principle:

Principle #5Merging (Combining)

4Volume of moving object

If large detector size is used to cover entire organ in one rotation, then volume coverage is improved, but device complexity and cost increase

Engineering Contradiction:

Improvevolume coverageVSAvoiddetector size

Core Design Contradiction:

Volume of moving objectVSDevice complexity

Solution Approach 1:

Instead of increasing detector size in the axial direction to cover the entire organ, the patent uses an additional spatial dimension by introducing linear trajectory motion. This allows comprehensive volume coverage through temporal-spatial sampling rather than requiring a large-area detector

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Data Source

PatentUS8270559B2Method and system for tomographic reconstruction in medical imaging using the circle and line trajectory

Publication Date: 2012.09.18 TOSHIBA MEDICAL SYST CORP

AI summary

A method of reconstructing a volume image of an object includes receiving circle projection data collected by a detector along a circular path with respect to the object; receiving line projection data collected by the detector along a linear path with respect to the object; producing a reconstructed circle path volume image of the object from the pre-processed circle projection data using a reconstruction algorithm that includes a ramp filter; producing a reconstructed line path volume image of the object from pre-processed line projection data using a reconstruction algorithm that includes a Hubert filter; and combining the reconstructed circle path volume image and the reconstructed line path volume image to produce the volume image of the object. An apparatus and computer program product are also described.