Skip to Content

Sponsors

No results

Tags

No results

Types

No results

Search Results

Events

No results
Search events using: keywords, sponsors, locations or event type
When / Where
All occurrences of this event have passed.
This listing is displayed for historical purposes.

Presented By: Nuclear Engineering and Radiological Sciences

PhD Defense: Jiyang Chu

Advanced Imaging Algorithms with Position-Sensitive Gamma-Ray Detectors

Title: Advanced Imaging Algorithms with Position-Sensitive Gamma-Ray Detectors

Chair: Prof. Zhong He

Abstract: The 3D position-sensitive CdZnTe detector can provide position and energy information of gamma-ray interactions, enabling imaging capability. Previous imaging methods can reconstruct distinguishable source locations. However, there exists a major contradiction in imaging problem eternally: information rate and reconstruction speed. The information rate represents how much information can be extracted from a measurement, including resolution, variance, and noise level. The reconstruction speed relies on the computing hardware heavily but can be greatly accelerated by sophisticated reconstruction algorithms. To improve the combined performance of information rate and reconstruction speed, several imaging algorithms were investigated. Among them, the Simple Back-Projection (SBP) provides fastest reconstruction speed but least information due to its biased and blurred estimation. The Filtered Back-Projection (FBP) is almost as fast as SBP, but much more informative. However, better understanding of FBP is required to let it work for real data without too much manual intervention, thus the adjusted FBP and the adaptive FBP were developed to make FBP practical. On the contrary, the Energy-Imaging Integrated Deconvolution (EIID) is a very informative reconstruction algorithm, but too slow to be applicable in many time-sensitive scenarios. The convergence rate of EIID should be accelerated without too much degradation to the information, thus the Energy-Decremental Integrated Deconvolution algorithm was developed. Finally, 3D image reconstruction is proposed, which provides a new dimension to interpret source distribution compared to traditional 2D spherical image reconstruction and is more natural for people to understand.

Explore Similar Events

  •  Loading Similar Events...

Back to Main Content