Architecture-Level Optimization on Digital Silicon Photomultipliers for Medical Imaging

Abstract

Silicon photomultipliers (SiPMs) are arrays of single-photon avalanche diodes (SPADs) connected in parallel. Analog silicon photomultipliers are built in custom technologies optimized for detection efficiency. Digital silicon photomultipliers are built in CMOS technology. Although CMOS SPADs are less sensitive, they can incorporate additional functionality at the sensor plane, which is required in some applications for an accurate detection in terms of energy, timestamp, and spatial location. This additional circuitry comprises active quenching and recharge circuits, pulse combining and counting logic, and a time-to-digital converter. This, together with the disconnection of defective SPADs, results in a reduction of the light-sensitive area. In addition, the pile-up of pulses, in space and in time, translates into additional efficiency losses that are inherent to digital SiPMs. The design of digital SiPMs must include some sort of optimization of the pixel architecture in order to maximize sensitivity. In this paper, we identify the most relevant variables that determine the influence of SPAD yield, fill factor loss, and spatial and temporal pile-up in the photon detection efficiency. An optimum of 8% is found for different pixel sizes. The potential benefits of molecular imaging of these optimized and small-sized pixels with independent timestamping capabilities are also analyzed.

Document Details

Document Type
Pub Defense Publication
Publication Date
Dec 24, 2021
Source ID
10.3390/s22010122

Entities

People

  • F. Bandi
  • Ion Vornicu
  • José María Benlloch Baviera
  • Ricardo Carmona-Galan
  • Victor Ilisie
  • Ángel Benito Rodríguez Vázquez

Organizations

  • European Research Council
  • Generalitat Valenciana
  • Ministry of Economy, Industry and Competitiveness
  • Office of Naval Research

Tags

Fields of Study

  • Physics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Image Processing and Computer Vision.
  • Integrated Circuit Design and Technology.

Technology Areas

  • Space