Office of Commercialization and Economic Development
Office of Technology Commercialization

Reconstruction of Super-Resolution Lung 4D-CT Using Patch-Based Sparse Representation

Technology #12-0105

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Researchers
Dinggang Shen
Managed By
Matthew Howe
Commercialization Manager 919.966.3929

A method has been developed to increase the resolution of 4D-CT scanning of moving organs such as the lung using a unique patch-based mechanism. This method has been extensively evaluated using the DIR-lab 4D-CT dataset. By analyzing intensity difference maps from a lung region at particular respiratory phases, it is clear that this method provided super resolution when compared to linear interpolation and cubic spline interpolation. Additionally, this method provided the highest peak signal-to-noise ratio, a measure used to evaluate the reconstruction error and representation fidelity. Because of the high-dose exposure associated with CT scans, dense sampling is often not practical, which leads to artifacts (such as lung vessel discontinuity) that can mislead dose administration of radiation therapy. This technology seeks to alleviate this problem by providing a novel technique for super-resolution enhancement along the superior-inferior direction. The premise of this technology is that the anatomical information that is missing at one particular phase can be recovered from other phases, allowing for the guided reconstruction of super-resolution axial slices. This technology helps design more accurate treatment plans for patients undergoing radiation therapy.

Advantages:

•  Many applications in radiotherapy of cancers, especially in organs that move with breathing such as the lung

•  Novel, patch-based representation provides a super-resolution 4D-CT image sequence with enhanced anatomical details

•  Outperforms linear and cubic-spline interpolation methods in terms of preserving image details

•  Suppresses misleading artifacts that can lead to suboptimal treatments for patients