Maximum-Likelihood--Based Position Decoding of Laser Processed Converging Pixel CsI: Tl Detectors for High-Resolution...

Area of Science:

• Medical Physics
• Nuclear Medicine
• Materials Science

Background:

• High spatial resolution is crucial for Single Photon Emission Computed Tomography (SPECT) imaging.
• Previous Laser Induced Optical Barrier (LIOB) methods achieved high resolution and yield in CsI: Tl detectors.
• Extending LIOB to a converging-pixel architecture offers potential for improved SPECT detector performance.

Purpose of the Study:

• To demonstrate the feasibility of a novel converging-pixel CsI: Tl detector fabrication technique for SPECT.
• To evaluate the performance of this new architecture using advanced decoding algorithms.
• To assess the potential for developing next-generation high-performance SPECT detectors.

Main Methods:

• Fabrication of a CsI: Tl crystal array with a converging-pixel architecture (1.6x1.6 mm2 entrance, 2x2 mm2 photodetector side).
• Implementation of Center of Gravity (CoG) and Maximum Likelihood (ML) based decoding algorithms for interaction localization.
• Utilizing a custom four-axis motion platform for precise beam delivery and data acquisition.

Main Results:

• Achieved an energy resolution of 11.79+/-0.53% in collimated experiments.
• Demonstrated a position localization accuracy of 1.00+/-0.42 mm using nearest neighbor interpolation.
• Validated the performance of the converging-pixel design with statistical decoding algorithms.

Conclusions:

• The novel converging-pixel CsI: Tl detector architecture is feasible for SPECT applications.
• Combining this architecture with statistical decoding algorithms significantly enhances SPECT detector performance.
• This approach represents a promising pathway for developing advanced, high-performance SPECT systems.