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A comparison study: image-based vs signal-based retrospective gating on microCT
- Source :
- Developments in X-Ray Tomography XI.
- Publication Year :
- 2017
- Publisher :
- SPIE, 2017.
-
Abstract
- Retrospective gating on animal studies with microCT has gained popularity in recent years. Previously, we use ECG signals for cardiac gating and breathing airflow or video signals of abdominal motion for respiratory gating. This method is adequate and works well for most applications. However, through the years, researchers have noticed some pitfalls in the method. For example, the additional signal acquisition step may increase failure rate in practice. X-Ray image-based gating, on the other hand, does not require any extra step in the scanning. Therefore we investigate imagebased gating techniques. This paper presents a comparison study of the image-based versus signal-based approach to retrospective gating. The two application areas we have studied are respiratory and cardiac imaging for both rats and mice. Image-based respiratory gating on microCT is relatively straightforward and has been done by several other researchers and groups. This method retrieves an intensity curve of a region of interest (ROI) placed in the lung area on all projections. From scans on our systems based on step-and-shoot scanning mode, we confirm that this method is very effective. A detailed comparison between image-based and signal-based gating methods is given. For cardiac gating, breathing motion is not negligible and has to be dealt with. Another difficulty in cardiac gating is the relatively smaller amplitude of cardiac movements comparing to the respirational movements, and the higher heart rate. Higher heart rate requires high speed image acquisition. We have been working on our systems to improve the acquisition speed. A dual gating technique has been developed to achieve adequate cardiac imaging.
Details
- Database :
- OpenAIRE
- Journal :
- Developments in X-Ray Tomography XI
- Accession number :
- edsair.doi...........7ec6c012a938674c210471d6aca6b08a