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Experimental Evaluation of Maximum-Likelihood-Based Data Preconditioning for DE-SPECT: A Clinical SPECT System
Yifei Jin1, E M Zannoni2, Ling-Jian Meng3
1Department of Nuclear, Plasma and Radiological Engineering, University of Illinois at Urbana-Champaign, Champaign, IL 61801 USA.
IEEE Transactions on Radiation and Plasma Medical Sciences
|September 2, 2025
Summary
A new maximum-likelihood method improves 3-D cadmium zinc telluride (CZT) detector imaging for peripheral vascular diseases. This technique addresses pixel boundary issues and spatial distortions in CZT detectors, enhancing image quality.
Area of Science:
- Medical Imaging
- Detector Physics
Background:
- Dynamic extremity-single photon emission computed tomography (SPECT) systems utilize 3-D position-sensitive cadmium zinc telluride (CZT) detectors for peripheral vascular disease imaging.
- High-resolution CZT detectors face challenges like pixel boundary effects, spatial distortions, and nonuniformity.
Purpose of the Study:
- To introduce a novel maximum-likelihood-based data preconditioning method for 3-D CZT detectors.
- To mitigate pixel boundary issues and correct spatial distortions and nonuniformity in CZT detector responses.
Main Methods:
- Developed a maximum-likelihood-based preconditioning technique for projection reconstruction.
- Utilized sheet-beam scanning to measure the distortion map of CZT detectors.
- Evaluated the technique through Tc-99m sheet-beam scanning and phantom image reconstruction.
Main Results:
- The proposed method effectively reduces the impact of pixel boundary issues.
- Spatial distortions and detector nonuniformity were corrected.
- Experimental evaluations demonstrated the technique's efficacy.
Conclusions:
- The maximum-likelihood-based preconditioning technique significantly enhances imaging performance of 3-D CZT detectors.
- This method shows potential for broad application across various imaging sensor types.
