Automatic exposure compensation in intraoral digital radiography: effect on the gray values of dental tissues

Background This study aimed to investigate the effect of automatic exposure compensation (AEC) of intraoral radiographic systems on the gray values of dental tissues in images acquired with or without high-density material in the exposed region using different exposure times and kilovoltages. The influence of the distance of the high-density material was also investigated. Methods Radiographs from the molar region of two mandibles were obtained using the RVG 6100 and the Express systems, operating at 60 and 70 kV and 0.06, 0.10, and 0.16 s. Subsequently, a titanium implant was inserted in the premolar’s socket and other images were acquired. Using the ImageJ software, two regions of interest were determined on the enamel, coronary dentine, root dentine, and pulp of the first and second molars to obtain their gray values. Results In the RVG 6100, the implant did not affect the gray values (p > 0.05); the increase in kV decreased it in all tissues (p < 0.05), and the exposure time affected only the root dentine and pulp. In the Express, only enamel and coronary dentine values changed (p < 0.05), decreasing with the implant presence and/or with the increase in exposure factors. The distance of the implant did not affect the results (p > 0.05). Conclusions AEC’s performance varies between the radiographic systems. Its effect on the gray values depends not only on the presence or absence of high-density material but also on the kV and exposure time used.

The Two-Stage Recognition Method Based on Texture Signals of the Heterogeneous Unsteady Iris

In this paper, a two-stage multi-category recognition structure based on texture features is proposed. This method can solve the problem of the decline in recognition accuracy in the scene of lightweight training samples. Besides, the problem of recognition effect different in the same recognition structure caused by the unsteady iris can also be solved. In this paper’s structure, digitized values of the edge shape in the iris texture of the image are set as the texture trend feature, while the differences between the gray values of the image obtained by convolution are set as the grayscale difference feature. Furthermore, the texture trend feature is used in the first-stage recognition. The template category that does not match the tested iris is the elimination category, and the remaining categories are uncertain categories. Whereas, in the second-stage recognition, uncertain categories are adopted to determine the iris recognition conclusion through the grayscale difference feature. Then, the experiment results using the JLU iris library show that the method in this paper can be highly efficient in multi-category heterogeneous iris recognition under lightweight training samples and unsteady state.

Development of MATLAB GUI Based on Blob Analysis for Automatic Extraction of Defects

This study introduces a graphical user interface (GUI) based on MATLAB to realize the automatic ex-traction of sizes of defects from the infrared sequence. To obtain the edge of the defect at deeper layer, a fusion stratagem of the maximum of gray values is adopted for an image subset in the sequence. Blob analysis to the fusion image is used to obtain the general information of defects of a specimen including the distributions and numbers of defects. The frame image is determined for a certain defect according to the peak of the time history curve of sensitive region variance. It can yield a region of interest (ROI) to expand the blob in the selected frame and the defect can be acquired by image segmentation. The results show that through this GUI, a better thermal image can be selected from a set of infrared sequence diagrams for quantitative extraction of different buried depth defect areas, which realizes automatic defect extraction, and its relative error is within 5%. The research on infrared automatic detection technology has certain significance.

Spatially Addressable Polarimetric Calibration of Reflective-Type Spatial Light Modulator Using Mueller–Stokes Polarimetry

Mueller–Stokes polarimetry is emerging as a prominent noninvasive imaging technique to study the structural characteristics of an anisotropic medium. Spatial light modulator (SLM) is a programmable liquid crystal device (LCD), which is used to modulate the amplitude, phase, and polarization of light. The compact design and cumbrous manufacturing process of SLM requires its polarimetric calibration prior to its utilization for various applications. In this study, we experimentally demonstrate Mueller–Stokes imaging of a reflective-type SLM (Holoeye, LCR-720) to calibrate its polarization modulation characteristics with respect to its dynamic gray value range (0–255) at different spatial locations of SLM screen. Mueller matrices at 18 different gray values of SLM at an interval of 15, that is, at gray values 0, 15, 30, up to 255 have been experimentally measured using an improvised Mueller matrix imaging polarimeter (MMIP). Crucial polarimetric characteristics, that is, diattenuation, polarizance, state of polarization (SOP), depolarization, and retardance have been estimated with respect to the gray value range of SLM. Significant polarization modulation characteristics [diattenuation (0.08–0.3), polarizance (0.02–0.2), and retardance (0 to π)] have been determined for the SLM. These results indicate that the SLM exhibits spatially variable depolarizing nature and hence it is not perfectly homogeneous in structure. Therefore, it is expected that the outcomes of this study would be helpful for exploring the applicability of Mueller–Stokes polarimetry in advancement of LC technology.

Can gray values be converted to Hounsfield units? A systematic review

Objectives: The purpose of this systematic review was to answer the focus question: “Could the gray values (GVs) from CBCT (cone beam computed tomography) be converted to Hounsfield units (HUs) in multidetector computed tomography (MDCT)?” Methods: The included studies try to answer the research question according to the PICO strategy. Studies were gathered by searching several electronic databases and partial grey literature up to January 2021 without language or time restrictions. The methodological assessment of the studies was performed using The Oral Health Assessment Tool (OHAT) for in vitro studies and the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) for in vivo studies. The Grading of Recommendations Assessment, Development and Evaluation (GRADE system) instrument was applied to assess the level of evidence across the studies. Results: 2710 articles were obtained in Phase 1, and 623 citations remained after removing duplicates. Only three studies were included in this review using a two-phase selection process and after applying the eligibility criteria. All studies were methodologically acceptable, although in general terms with low risks of bias. There are some included studies with quite low and limited evidence estimations and recommendation forces; evidencing the need for clinical studies with diagnostic capacity to support its use. Conclusions: This systematic review demonstrated that the GVs from CBCT cannot be converted to HUs due to the lack of clinical studies with diagnostic capacity to support its use. However, it is evidenced that three conversion steps (equipment calibration, prediction equation models, and a standard formula (converting GVs to HUs)) are needed to obtain pseudo Hounsfield values instead of only obtaining them from a regression or directly from the software.

Quantitative Evaluation of Unfilled Grout in Tendons of Prestressed Concrete Girder Bridges by Portable 950 keV/3.95 MeV X-ray Sources

We have developed porTable 950 keV/3.95 MeV X-band (9.3 GHz) electron linear accelerator (LINAC)-based X-ray sources and conducted onsite prestressed concrete (PC) bridge inspection in the last 10 years. A T-shaped PC girder bridge with a thickness of 200–400 mm and a box-shaped PC girder bridge with a thickness of 200–800 mm were tested. X-ray transmission images of flaws such as thinning, fray, and disconnection caused by corrosion of PC wires and unfilled grout were observed. A three-dimensional structural analysis was performed to estimate the reduction in the yield stress of the bridge. In this study, we attempted to evaluate the unfilled grout quantitatively because it is the main flaw that results in water filling and corrosion. In the measured X-ray images, we obtained gray values, which correspond to the X-ray attenuation coefficients of filled/unfilled grouts, PC wires (steel) in a sheath, and concrete. Then, we compared the ratio of the gray values of the filled/unfilled grouts and PC wires to determine the stage of the unfilled grout. We examined this quantitative evaluation using the data obtained from a real T-shaped PC girder bridge and model samples to simulate thick box-shaped PC girder bridges. We obtained a clear quantitative difference in the ratios for unfilled and filled grouts, which coincided with our visual perception. We synthesized the experience and data and proposed a quantitative analysis for evaluating the unfilled grout for subsequent steps such as structural analysis and destructive evaluation by boring surveys.

Value of conventional magnetic resonance imaging texture analysis in the differential diagnosis of benign and borderline/malignant phyllodes tumors of the breast

Background The purpose of this study was to determine the potential value of magnetic resonance imaging (MRI) texture analysis (TA) in differentiating between benign and borderline/malignant phyllodes tumors of the breast. Methods The preoperative MRI data of 25 patients with benign phyllodes tumors (BPTs) and 19 patients with borderline/malignant phyllodes tumors (BMPTs) were retrospectively analyzed. A gray-level histogram and gray-level cooccurrence matrix (GLCM) were used for TA with fat-suppressed T2-weighted imaging (FS-T2WI), diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) images, and 2- and 7-min postcontrast T1W images on dynamic contrast-enhanced MRI (DCE-T1WI2min and DCE-T1WI7min) between BPTs and BMPTs. Independent sample t-test and Mann-Whitney U test were performed for intergroup comparison. A regression model was established by using binary logistic regression analysis, and receiver operating characteristic (ROC) curve analysis was carried out to evaluate diagnostic efficiency. Results For ADC images, the texture parameters angular second moment (ASM), correlation, contrast, entropy and the minimum gray values of ADC images (ADCMinimum) showed significant differences between the BPT group and BMPT group (all p<0.05). The parameter entropy of FS-T2WI and the maximum gray values and kurtosis of the tumor solid region of DCE-T1WI7min also showed significant differences between these two groups. Except for ADCMinimum, angular second moment of FS-T2WI (FS-T2WIASM), and the maximum gray values of DCE-T1WI7min (DCE-T1WI7min-Maximum) of the tumor solid region, the AUC values of other positive texture parameters mentioned above were greater than 0.75. Binary logistic regression analysis demonstrated that the contrast of ADC images (ADCContrast) and entropy of FS-T2WI (FS-T2WIEntropy) could be considered independent texture variables for the differential diagnosis of BPTs and BMPTs. Combined, the AUC of these parameters was 0.891 (95% CI: 0.793–0.988), with a sensitivity of 84.2% and a specificity of up to 89.0%. Conclusion Texture analysis could be helpful in improving the diagnostic efficacy of conventional MR images in differentiating BPTs and BMPTs.

Benefits of using a photostimulable phosphor plate protective device

Objectives: To develop and test a protective device (PD) to increase the resistance of photostimulable storage phosphor (PSP) plate to compressive load, and assess the resulting image quality. Methods: Two prototypes, polyvinylchloride sheets of 0.3 mm and 0.7 mm each, were developed for PSP plate size 2. The resistance to compressive load was tested using eight new PSPs divided into four test groups: (1) PSP, (2) PSP and paperboard protector, (3) PSP and 0.3 mm PD, and (4) PSP and 0.7 mm PD. The resulting images were analyzed by three oral radiologists, based on the consensus for image artifacts. Additionally, the objective image quality test was performed with four new PSPs, using an 8-step wedge aluminum scale. The mean gray values and standard deviation were measured in a total of 240 images, and the data were analyzed using analysis of variance with Bonferroni post-hoc test. Results: Artifacts were seen in the PSP control group starting at 40 n, and at 150 n, 175 n and 300 n in 0.3 mm PD, paperboard protector and 0.7 mm PD, respectively. Although there was no statistical difference among groups, there were differences between exposure times (0.06–0.25 s, 0.06–0.40 s, and 0.10–0.40 s). Scanning resolution of 20 lp/mm showed higher mean gray value than 25 and 40 lp/mm (p < 0.05) Conclusion: The developed PDs improved the PSP resistance to compressive forces, with low interference on the pixel gray values, regardless of exposure time and spatial resolution. Nevertheless, the 0.7 mm PD could withstand the maximum compressive load.

Automatic Segmentation of Remote Sensing Images on Water Bodies Based on Image Enhancement

By virtue of high-resolution remote sensing satellites, there is a possibility to analyze remote sensing images on water bodies through digital image processing (DIP). In many remote sensing images, however, the water bodies have similar gray values as other ground objects. To effectively distinguish water bodies from other ground objects in these images, this paper proposes a logarithmic enhancement method for remote sensing images on water bodies based on adaptive morphology. The proposed method can filter the noise of non-target area, and enhance the water body in the original image. On this basis, a morphology-based segmentation method was designed for remote sensing images on water bodies. Experimental results show that our method achieved a high segmentation accuracy, controlling the mean segmentation error at below 1.32%.