Assessment of an in-house phantom for the quality control of a clinical gamma camera

Optimizing the Minimum Detectable Difference of Gamma Camera SPECT Images via the Taguchi Analysis: A Feasibility Study with a V-Shaped Slit Gauge

This study tried to propose an innovated idea of solidifying the resolution of gamma camera in routine quality control and recommended a quantified index as minimum detectable difference (MDD) of gamma camera SPECT images using the Taguchi analysis and an indigenous V-shaped slit gauge. The gauge was customized to fulfill the quantitative requirement of the Taguchi analysis. The MDD among slit gauge of derived SPECT image was calculated from two overlapped peak profiles collected from a tangent slice of the V-shaped slit gauge with two nearby peaks. In particular, MDD was evaluated as minimum distance between two peak centers through the Student’s t-test with a constant, 1.96, which indicates that two peak centers separated distant enough to create a 95% confidence level of separation. Eighteen combinations of six gamma camera scanned factors were organized according to Taguchi analysis. Accordingly, (A) collimator, (B) detector to targe distance, (C) total counts, (D) acquired energy width, (E) Matrix size, and (F) zoom of collected ROI with each of two or three levels were organized into 18 groups to collect the slit gauge images according to Taguchi L18 orthogonal array. Then, three well-trained radiologists were ranked the scanned gauge images to derive the fish-bone-plot of signal-to-noise ratio (S/N, dB) and correlated ANOVA. Furthermore, the quantified MDD was proposed to verify the optimal suggestion of gamma camera scanned protocol, and obtained the MDD as 8.4, 7.9, and 7.1 mm for the second group of original L18 preset, conventional, and the optimal preset, respectively. Thus, the optimal preset of gamma camera was achieved in this study. The MDD proved to be a successful index in quantifying the imaging resolution of a gamma camera.

Multi-exposure X-ray image fusion quality evaluation based on CSF and gradient amplitude similarity

Due to the limitation of dynamic range of the imaging device, the fixed-voltage X-ray images often produce overexposed or underexposed regions. Some structure information of the composite steel component is lost. This problem can be solved by fusing the multi-exposure X-ray images taken by using different voltages in order to produce images with more detailed structures or information. Due to the lack of research on multi-exposure X-ray image fusion technology, there is no evaluation method specially for multi-exposure X-ray image fusion. For the multi-exposure X-ray fusion images obtained by different fusion algorithms may have problems such as the detail loss and structure disorder. To address these problems, this study proposes a new multi-exposure X-ray image fusion quality evaluation method based on contrast sensitivity function (CSF) and gradient amplitude similarity. First, with the idea of information fusion, multiple reference images are fused into a new reference image. Next, the gradient amplitude similarity between the new reference image and the test image is calculated. Then, the whole evaluation value can be obtained by weighting CSF. In the experiments of MEF Database, the SROCC of the proposed algorithm is about 0.8914, and the PLCC is about 0.9287, which shows that the proposed algorithm is more consistent with subjective perception in MEF Database. Thus, this study demonstrates a new objective evaluation method, which generates the results that are consistent with the subjective feelings of human eyes.