Sub-2 mm depth of interaction localization in PET detectors with prismatoid light guide arrays and single-ended readout using convolutional neural networks.

Journal: Medical physics
Published Date: Feb 2, 2021

Abstract

PURPOSE: Depth of interaction (DOI) readout in PET imaging has been researched in efforts to mitigate parallax error, which would enable the development of small diameter, high-resolution PET scanners. However, DOI PET has not yet been commercialized due to the lack of practical, cost-effective, and data efficient DOI readout methods. The rationale for this study was to develop a supervised machine learning algorithm for DOI estimation in PET that can be trained and deployed on unique sets of crystals.

Authors

  • Andy LaBella
    Department of Radiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, USA.
  • Xinjie Cao
    Department of Electrical and Computer Engineering, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, NY, USA.
  • Xinjie Zeng
    Department of Electrical and Computer Engineering, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, NY, USA.
  • Wei Zhao
    Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, Jiangnan University, Wuxi 214122, Jiangsu Province, P. R. China. lxy@jiangnan.edu.cn zhuye@jiangnan.edu.cn.
  • Amir H Goldan
    Department of Radiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, USA.

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