Positron Emission Tomography (PET) scanners provide functional three-dimensional images of the body that are extremely useful in cancer and brain research. The goal of this work is the modeling, design and characterization of a CMOS-based photodetector for PET. To this aim, first a model for the energy resolution and coincidence resolution time (CRT) for digital, SPAD-based detectors is developed. Then, a top-to-bottom detector architecture is proposed, containing an innovative in-pixel com-pression technique that allows for high fill-factor (FF) and efficient readout. At the top-level of the architecture, an integrated discriminator monitors the photon flux for incoming gamma events, enabling an event-based readout scheme. The first complete implementation of this archi-tecture is described, the SPADnet-I sensor, which is composed by an 8×16 pixel array, each of around 0.6 × 0.6 mm2 with 720 SPADs, resulting in a pixel FF of 42.6%. The sensor can obtain the discrete photon flux estimation at up to 100 Msamples/s, which are used by the discriminator and also output at real-time. The complete characterization of the sensor is presented, and the best sensor configuration was found to be at 84% of the SPADs enabled (disabled starting with the highest DCR one), with 2 V SPAD excess bias and 150 ns integration time. This configuration results in an energy resolution of 10.8% and a CRT of 288 ps, the latter which was obtained with a new, hardware-friendly time of arrival (ToA) estimation algorithm, also described in this thesis. Finally, the sensor model, validated by the experimental results, is used to predict the perfor-mance of possible modifications in the sensor, and some design improvements are suggested for a future implementation of the architecture.

Modeling, Design and Characterization of a Multi-Pixel Digital SiPM for PET Applications / Huf Campos Braga, Leo. - (2014), pp. 1-123.

Modeling, Design and Characterization of a Multi-Pixel Digital SiPM for PET Applications

Huf Campos Braga, Leo
2014-01-01

Abstract

Positron Emission Tomography (PET) scanners provide functional three-dimensional images of the body that are extremely useful in cancer and brain research. The goal of this work is the modeling, design and characterization of a CMOS-based photodetector for PET. To this aim, first a model for the energy resolution and coincidence resolution time (CRT) for digital, SPAD-based detectors is developed. Then, a top-to-bottom detector architecture is proposed, containing an innovative in-pixel com-pression technique that allows for high fill-factor (FF) and efficient readout. At the top-level of the architecture, an integrated discriminator monitors the photon flux for incoming gamma events, enabling an event-based readout scheme. The first complete implementation of this archi-tecture is described, the SPADnet-I sensor, which is composed by an 8×16 pixel array, each of around 0.6 × 0.6 mm2 with 720 SPADs, resulting in a pixel FF of 42.6%. The sensor can obtain the discrete photon flux estimation at up to 100 Msamples/s, which are used by the discriminator and also output at real-time. The complete characterization of the sensor is presented, and the best sensor configuration was found to be at 84% of the SPADs enabled (disabled starting with the highest DCR one), with 2 V SPAD excess bias and 150 ns integration time. This configuration results in an energy resolution of 10.8% and a CRT of 288 ps, the latter which was obtained with a new, hardware-friendly time of arrival (ToA) estimation algorithm, also described in this thesis. Finally, the sensor model, validated by the experimental results, is used to predict the perfor-mance of possible modifications in the sensor, and some design improvements are suggested for a future implementation of the architecture.
2014
XXVI
2013-2014
Ingegneria e scienza dell'Informaz (29/10/12-)
Information and Communication Technology
Stoppa, David
no
Inglese
Settore ING-INF/01 - Elettronica
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/369044
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