An evaluation of cusum analysis and control charts applied to quantitative gamma-camera uniformity parameters for automated quality control

Abstract

Gamma-camera uniformity is often monitored for quality control of performance. Many parameters can be derived from computer analysis of the image of a uniform (flood) source to obtain quantitative measures of uniformity. However, it is not clear which best reflect changes in uniformity, or how action levels should be set. The latter are essential for an automated analysis. To compare the various parameters and assess two techniques used for their analysis, a series of technetium-99m flood images were obtained consecutively. After establishing a baseline from repeated images, uniformity was degraded by offsetting the pulse height analyser (PHA) window by a small amount. Nine non-uniformity parameters were calculated for each flood image, including the Department of Health and Social Security (DHSS) and National Electrical Manufacturers Association (NEMA) integral and differential uniformities, the uniformity index and the percentage of pixels more than 5% from the mean. All parameters were calculated for both central field-of-view (CFOV) and useful field-of-view (UFOV). Eighty such trials were carried out on two gamma-cameras. The PHA offsets ranged from 1-10 keV. The two techniques used for analysis were the control chart and cusum analysis. Decision levels were set for each parameter, as multiples of SD for the control charts or by varying the dimensions of a truncated V-mask for cusum analysis. Receiver operating characteristic (ROC) curves were then used for an objective comparison of the parameters and of the analysis techniques. The area under the ROC curve was used to rank the parameters in order of sensitivity to change in uniformity.(ABSTRACT TRUNCATED AT 250 WORDS)

Method for automatic detection of defective ultrasound linear array transducers based on uniformity assessment of clinical images — A case study

“…Assessment of the image uniformity as part of a quality assurance program is used for other imaging modalities as well, such as e.g., computed 26,27 and digital 28 radiography systems and in nuclear medicine. 29,30 To use median images of clinical images for detecting nonuniformities in these systems may also be possible, and could be useful as a complement to quality assurance for early detection of a subset of defects. For systems where the examined part of the patient does not cover the whole detector, or where the examined part like bones or lungs mostly covers the same part of the detector, the median image becomes nonuniform in itself.…”

Improved Nuclear Medicine Uniformity Assessment with Noise Texture Analysis

“…This method was initially devised as a standardized method with which manufacturers could state their system specifications. Because of its ease of calculation and reproducibility across multiple manufacturer platforms, this basic method has become widely used in daily quality control uniformity analysis (12).…”

The Radon transform, its generalization and their applications in PET and SPECT medical imaging

“…and λ is a user-defined positive number (namely the multiplier of the SD), conventionally set at λ = 3, but any λ may be used [87]. The value of λ is related to the size of the persistent shift we are interested to detect and the smaller the size the smaller the value of λ.…”