  Fault detection and diagnosis is critical to many applications in order to
ensure proper operation and performance over time. Positron emission tomography
(PET) systems that require regular calibrations by qualified scanner operators
are good candidates for such continuous improvements. Furthermore, for scanners
employing one-to-one coupling of crystals to photodetectors to achieve enhanced
spatial resolution and contrast, the calibration task is even more daunting
because of the large number of independent channels involved. To cope with the
additional complexity of the calibration and quality control procedures of
these scanners, an intelligent system (IS) was designed to perform fault
detection and diagnosis (FDD) of malfunctioning channels. The IS can be broken
down into four hierarchical modules: parameter extraction, channel fault
detection, fault prioritization and diagnosis. Of these modules, the first two
have previously been reported and this paper focuses on fault prioritization
and diagnosis. The purpose of the fault prioritization module is to help the
operator to zero in on the faults that need immediate attention. The fault
diagnosis module will then identify the causes of the malfunction and propose
an explanation of the reasons that lead to the diagnosis. The FDD system was
implemented on a LabPET avalanche photodiode (APD)-based digital PET scanner.
Experiments demonstrated a FDD Sensitivity of 99.3 % (with a 95% confidence
interval (CI) of: [98.7, 99.9]) for major faults. Globally, the Balanced
Accuracy of the diagnosis for varying fault severities is 92 %. This suggests
the IS can greatly benefit the operators in their maintenance task.
