Image Quality Figures Research Articles

Self-normalization for a 1 mm3 resolution clinical PET system using deep learning

Objective. This work proposes, for the first time, an image-based end-to-end self-normalization framework for positron emission tomography (PET) using conditional generative adversarial networks (cGANs). Approach. We evaluated different approaches by exploring each of the following three methodologies. First, we used images that were either unnormalized or corrected for geometric factors, which encompass all time-invariant factors, as input data types. Second, we set the input tensor shape as either a single axial slice (2D) or three contiguous axial slices (2.5D). Third, we chose either Pix2Pix or polarized self-attention (PSA) Pix2Pix, which we developed for this work, as a deep learning network. The targets for all approaches were the axial slices of images normalized using the direct normalization method. We performed Monte Carlo simulations of ten voxelized phantoms with the SimSET simulation tool and produced 26,000 pairs of axial image slices for training and testing. Main results. The results showed that 2.5D PSA Pix2Pix trained with geometric-factors-corrected input images achieved the best performance among all the methods we tested. All approaches improved general image quality figures of merit peak signal to noise ratio (PSNR) and structural similarity index (SSIM) from ∼15 % to ∼55 %, and 2.5D PSA Pix2Pix showed the highest PSNR (28.074) and SSIM (0.921). Lesion detectability, measured with region of interest (ROI) PSNR, SSIM, normalized contrast recovery coefficient, and contrast-to-noise ratio, was generally improved for all approaches, and 2.5D PSA Pix2Pix trained with geometric-factors-corrected input images achieved the highest ROI PSNR (28.920) and SSIM (0.973). Significance. This study demonstrates the potential of an image-based end-to-end self-normalization framework using cGANs for improving PET image quality and lesion detectability without the need for separate normalization scans.

Detectability of category 3 or higher microcalcifications on digital mammograms: a comparative study between 5-MP color and monochrome liquid crystal display monitors.

This study explored the detectability of category 3 or higher microcalcifications using 5-MP color and monochrome monitors. Contrast detail mammography phantom with polymethyl methacrylate (PMMA) images were observed in color and monochrome by five radiographers, and the image quality figures (IQF) were calculated based on the gold disc locations identified. Five radiographers and two radiologists observed 200 mammograms from 100 patients (including 36 with microcalcifications) and rated the microcalcifications. The results were analyzed using area under the curve (AUC) and jackknife resampling. A paired t test was used for statistical analysis (p < 0.05). The mean IQF of color and monochrome monitors were 10.73 and 10.49 (30mm PMMA, p = 0.653) and 8.47 and 8.74 (50mm PMMA, p = 0.774), respectively. The mean AUC of color and monochrome monitors were 0.917 and 0.936 (p = 0.335), respectively, with windowing and magnification. The detectability of microcalcifications was not significantly different between the monitors.

Evaluating clinical implications of 15-mega-sub-pixel liquid-crystal display in phase-contrast mammography

Phase-contrast mammography (PCM) systems characteristically yield sharp images with edge enhancement and high-resolution 25-μm/pixel mammograms. However, not all PCM image information can be shown on the display at a resolution of 5-megapixel (5-MP), although 5-MP monitors are recommended for interpretation of digital mammograms. Therefore, we investigated the potential utility of a 15-mega-sub-pixel (15-MsP) display for PCM images. We used a monitor that offered both 5-MP and 15-MsP displays by using a sub-pixel drive (SPD) technique to increase the spatial resolution of the monitor by threefold in the direction of the sub-pixels. Contrast-detail mammography phantom images were evaluated visually by four radiologic technologists. In this study, four display magnification ratios were used and the calculated image quality figures (IQFs) were compared with those of a 5-MP display. The detection capability of the 15-MsP display was significantly better than that of the 5-MP display at magnification ratios of 49 and 100%. At other magnification ratios, the detection capability of the 15-MsP display was higher than that of the 5-MP display, but the difference was not significant. A 15-MsP display has the potential to provide better detection than that provided by conventional 5-MP displays. A 15-MsP display using SPD technology is suitable for high-resolution digital mammograms, such as those produced by PCM systems.

Implementation and evaluation of an expectation maximization reconstruction algorithm for gamma emission breast tomosynthesis

We are developing a dual modality tomosynthesis breast scanner in which x-ray transmission tomosynthesis and gamma emission tomosynthesis are performed sequentially with the breast in a common configuration. In both modalities projection data are obtained over an angular range of less than 180° from one side of the mildly compressed breast resulting in incomplete and asymmetrical sampling. The objective of this work is to implement and evaluate a maximum likelihood expectation maximization (MLEM) reconstruction algorithm for gamma emission breast tomosynthesis (GEBT). A combination of Monte Carlo simulations and phantom experiments was used to test the MLEM algorithm for GEBT. The algorithm utilizes prior information obtained from the x-ray breast tomosynthesis scan to partially compensate for the incomplete angular sampling and to perform attenuation correction (AC) and resolution recovery (RR). System spatial resolution, image artifacts, lesion contrast, and signal to noise ratio (SNR) were measured as image quality figures of merit. To test the robustness of the reconstruction algorithm and to assess the relative impacts of correction techniques with changing angular range, simulations and experiments were both performed using acquisition angular ranges of 45°, 90° and 135°. For comparison, a single projection containing the same total number of counts as the full GEBT scan was also obtained to simulate planar breast scintigraphy. The in-plane spatial resolution of the reconstructed GEBT images is independent of source position within the reconstructed volume and independent of acquisition angular range. For 45° acquisitions, spatial resolution in the depth dimension (the direction of breast compression) is degraded with increasing source depth (increasing distance from the collimator surface). Increasing the acquisition angular range from 45° to 135° both greatly reduces this depth dependence and improves the average depth dimension resolution from 10.8 to 4.8 mm. The 135° acquisition results in a near-isotropic, spatially uniform 3D resolution of approximately 4.3 mm full width at half maximum. Background nonuniformity (cupping) artifacts arise primarily from angular incompleteness for small angular range acquisition but primarily from gamma ray attenuation at larger angular range. However, background artifacts can be largely eliminated if both prior information regularization and AC are applied. An artificial decrease in lesion voxel value with increasing lesion depth can also be substantially reduced through a combination of AC and RR. In experiments using compressible gelatin breast phantoms, lesion contrast and SNR are about 2.6-8.8 times and 2.3-5.6 times higher, respectively, in GEBT than in planar breast scintigraphy depending on the acquisition angle, the gamma camera trajectory, and the lesion location. In addition, the strong reduction in lesion contrast and SNR with increasing lesion depth that is observed in planar breast scintigraphy can be largely overcome in GEBT. The authors have demonstrated a promising EM-based reconstruction scheme for use in GEBT. Compared to planar breast scintigraphy GEBT provides superior and less position-dependent lesion contrast, lesion SNR, and spatial resolution as well as more accurate quantification of lesion-to-background activity concentration ratio.

Quantification of image quality using information theory

Aims of present study were to examine usefulness of information theory in visual assessment of image quality. We applied first order approximation of the Shannon's information theory to compute information losses (IL). Images of a contrast-detail mammography (CDMAM) phantom were acquired with computed radiographies for various radiation doses. Information content was defined as the entropy Σp( i )log(1/p ( i )), in which detection probabilities p ( i ) were calculated from distribution of detection rate of the CDMAM. IL was defined as the difference between information content and information obtained. IL decreased with increases in the disk diameters (P < 0.0001, ANOVA) and in the radiation doses (P < 0.002, F-test). Sums of IL, which we call total information losses (TIL), were closely correlated with the image quality figures (r = 0.985). TIL was dependent on the distribution of image reading ability of each examinee, even when average reading ratio was the same in the group. TIL was shown to be sensitive to the observers' distribution of image readings and was expected to improve the evaluation of image quality.

Fractal-feature distance analysis of contrast-detail phantom image and meaning of pseudo fractal dimension and complexity

The purposes of our studies are to examine whether or not fractal-feature distance deduced from virtual volume method can simulate observer performance indices and to investigate the physical meaning of pseudo fractal dimension and complexity. Contrast-detail (C-D) phantom radiographs were obtained at various mAs values (0.5 - 4.0 mAs) and 140 kVp with a computed radiography system, and the reference image was acquired at 13 mAs. For all C-D images, fractal analysis was conducted using the virtual volume method that was devised with a fractional Brownian motion model. The fractal-feature distances between the considered and reference images were calculated using pseudo fractal dimension and complexity. Further, we have performed the C-D analysis in which ten radiologists participated, and compared the fractal-feature distances with the image quality figures (IQF). To clarify the physical meaning of the pseudo fractal dimension and complexity, contrast-to-noise ratio (CNR) and standard deviation (SD) of images noise were calculated for each mAs and compared with the pseudo fractal dimension and complexity, respectively. A strong linear correlation was found between the fractal-feature distance and IQF. The pseudo fractal dimensions became large as CNR increased. Further, a linear correlation was found between the exponential complexity and image noise SD.

Pediatric digital chest radiography, comparison of grid versus non-grid techniques

Introduction The usefulness of anti-scatter grid in digital pediatric chest radiography was investigated by a phantom study assessing image quality using subjective evaluations and dose measurements. Method A contrast detail study was undertaken. Images were taken with and without anti-scatter grids (grid ratio 15:1), for PMMA phantom thickness ranging from 1 to 15 cm. Fourteen radiographers, experienced in digital pediatric and/or skeletal radiography, read 96 images. At each thickness, the image with and without grid technique was read three times, and in random order. Correct Observation Ratio (COR) and Image Quality Figures (IQF) were calculated. Dose Area Products were measured with DAP-meter. Results The COR and IQF values indicated statistically significant ( p < 0.05) enhanced image quality when using anti-scatter grid for all thicknesses 5 cm and more. The DAP values increased significantly by grid techniques ( p = 0.01). Conclusions Grid techniques may be beneficial to image quality for PMMA objects over 5 cm, but this leads to a higher dose. Although the magnitude of dose may be low, the dose should be kept at a minimum. In conclusion, improving image quality should be based on optimizing post-processing settings and image evaluation conditions.

SU-FF-I-72: Evaluation and Comparison of Image Quality Figures for Digital Mammography

Purpose: To survey the image quality of digital mammographic units in Taiwan using a mammographic contrast‐detail phantom and an ACR accreditation phantom, and to compare image quality figures from those two phantoms. Method and Materials: The scope of the survey covered most digital mammographic units in Taiwan. On‐site measurements included phantom image acquisitions and entrance surface doses (ESD).Image acquisitions of an ACR accreditation phantom (Victoreen N‐566 18‐220) and ESD measurements were following the protocols of the ACR MammographyQuality Control Manual. A mammographic contrast‐detail phantom (CDMAM type 3.4, Artinis) with 1‐cm PMMA‐equivalent thickness was placed on the PMMA of 3 cm. The CDMAM assembling was exposed using the same technical factors as the ACR accreditation phantom. Signal‐difference‐to‐noise Ratios (SDNR) of the largest mass inside the ACR phantom were calculated by the equation, SDNR = (Mean background − Mean mass )/ (SD background 2 + SD mass 2 ) . Inverse Image quality figures (IQFinv) were calculated according to the threshold diameter (D i,min) at each contrast‐column (Ci ), IQF inv = n/Σ(D i,min ⋅C i ) . Results: Fifty‐seven digital units were surveyed, including 44 DR units and 13 CR units. The tube voltage, tube current‐time product, and ESD range from 23 to 29 kV, 36 to 182 mAs, and 3.22 to 12.4 mGy for imaging the ACR phantom. The mean values and standard deviation of SDNR are 1.97±0.31 for GE 2000D, 1.50±0.91 for GE DS, and 1.76±0.20 for Hologic Lorad Selenia. The mean values and standard deviation of IQFinv are 127±10 for GE 2000D, 120±11 for GE DS, 135±28 for Hologic Lorad Selenia, and 101±0 for Siemens Novation DR. The correlation between SNDR and IQF are mild (R 2=0.414 for GE 2000D; 0.520, GE DS; 0.446, Hologic Lorad Selenia). Conclusion: The SNDR obtained from the ACR phantom mildly correlates with the IQFinv evaluated from the CDMAM phantom.

Image quality assessment using the CD-DISC phantom for vascular radiology and vascular surgery

The purpose of the study was to evaluate image quality (IQ) associated with vascular radiology and vascular surgery procedures in Belgium and to determine reference values for future image quality assessment. IQ was evaluated with the CD-DISC contrast-detail phantom. This circular PMMA phantom contains 225 holes with different diameter and depth, to quantify resolution and contrast. Images of the phantom were acquired for both fluoroscopy and subtraction images on 21 systems. Three observers evaluated the images by determining the threshold contrast visible for every diameter. This results in contrast-detail curves and image quality figures. We observed a large difference in IQ between the centres. No straightforward correlation could be found with radiation dose or other exposure settings. A comparison was made with the image quality evaluation of the systems performed with the TOR[18FG] phantom for fluoroscopy. There is no clear correlation observed between the results of the CD-DISC phantom and the TOR phantom. However, systems with very poor or very good image quality could be detected by both phantoms. An important result is that a 75th percentile reference contrast-detail curve could be proposed to separate the best centres from these with poorer quality. Some centres had also a significantly better image quality than others. Therefore, we introduced also a 25th percentile. Centres with IQ above this value are recommended to lower the dose and work with acceptable rather than excellent image quality. The CD-DISC phantom thus allows to guide the image quality setting.

Fractal-feature distance as a substitute for observer performance index in contrast-detail examination

Purpose To assess whether or not the fractal-feature distance using the box-counting algorithm can be a substitute for observer performance index. Methods and materials Contrast-detail (C-D) phantom images were obtained at various mAs-values (0.5–4.0 mAs) and 140 kV p with a Fuji computed radiography system, and the reference image was acquired at 50 mAs; all cylindrical targets in the C-D phantom were visualized on this image. The C-D images were converted to binary images using the profile curves around the smallest cylindrical target images on the reference images. The fractal analysis was conducted using the box-counting algorithm for these binary images. The fractal-feature distances between the low-dose and reference images were calculated using the fractal dimension and the complexity. Furthermore, we performed the C-D analysis in which ten radiologists participated, and compared the fractal-feature distances with the image quality figures (IQF) derived from the C-D analysis with Markov chain. Results For all C-D phantom radiographs, the relationship between the length of the square boxes and the number of boxes to cover the positive pixels of the binary image was linear on a log–log scale ( r ≥ 0.999). A strong linear correlation was found between the fractal-feature distance and IQF ( r = 0.990). Conclusion We have shown that the binary image of C-D phantom can be analyzed by the box-counting algorithm and its fractal-feature distance increases as the radiation dose decreases. Furthermore, we have shown that the fractal-feature distances will be equivalent to IQFs in C-D analysis.

直接型ＦＰＤの画質特性と検出特性

The physical characteristics of a direct amorphous Selenium (a-Se) digital fluoroscopy and radiography system were investigated. Pre-sampled modulation transfer functions (MTF) were measured using a slit method. Noise power spectra were determined for different input exposures by fast Fourier transform of uniformly exposed samples. The MTFs of direct digital radiography systems showed significantly higher values than those of indirect digital radiography and screen-film systems. The direct digital radiography systems showed higher noise levels compared with those of indirect systems under roughly the same exposure conditions. Contrast-detail analysis was performed to compare detection by direct digital radiography systems with that of the screen-film (FUJI HG-M2/UR2) systems. The average contrast-detail curves of digital and film images were obtained from the results of observation. Image quality figures (IQF) were also calculated from the individual observer performance tests. The results indicated that digital contrast-detail curves and IQF are, on average, are equal those of the screen-film system.

Full-field digital mammography with amorphous silicon-based flat- panel detector: physical imaging characteristics and signal detection

The physical characteristics of a clinical amorphous silicon-based flat-panel imager for full-field digital mammography were investigated. Pre-sampled modulation transfer functions (MTF) were measured by using a slit method. Noise power spectra were determined for different input exposures by fast Fourier transform. The MTFs of full-field digital mammography systems showed significantly higher values than those of the computed radiography (CR) system. The full-field digital mammography system showed a lower noise level than that of the CR system under the same exposure conditions. Contrast detail analysis has been performed to compare the detectability of the full-field digital mammography system with that of the screen-film (Min-R 2000/Min-R 2000) system. The average contrast-detail curves of digital and film images were obtained from the results of observation. Image quality figures (IQF) were also calculated from the individual observer performance tests. The results indicated that the digital contrast-detail curves and IQF, on average, are superior to those of the screen-film system.