Contrast-to-noise ratio in magnification mammography: a Monte Carlo study

Performance and usefulness evaluation of a software-based scatter correction technique for mammographic images

Although physical grids improve contrast in radiographic images by reducing scattered radiation, various artifacts such as grid shadow, moire, and cutoff result in increased patient doses. To overcome these problems, this study evaluates the applicability and usefulness of a material thickness-based scatter-correction technique for mammography. Specifically, this study aims to compare and evaluate the performance of mammography using the proposed software-based scatter correction framework and a physical grid. The proposed technique enables scatter correction based on pre-calculated parameters of a thickness-based scatter kernel at a water slab phantom and an empirical quantity of scatter components in a mammographic system. In the Monte Carlo simulation and experiment, the proposed framework displayed an intensity profile and full width at half maximum that closely approximated those seen in the physical grid. In addition, by applying the proposed framework to the ACR phantom, it was verified that all structures, including specks, were distinctly distinguished. The results demonstrate that the X-ray scatter-correction method with a software-based framework for mammography is applicable to the field of diagnostic imaging, as this approach yields image quality equivalent to that achieved with physical grids while also enabling a reduction in radiation doses for patients.

Development of Adaptive Point-Spread Function Estimation Method in Various Scintillation Detector Thickness for X-ray Imaging

An indirect conversion X-ray detector uses a scintillator that utilizes the proportionality of the intensity of incident radiation to the amount of visible light emitted. A thicker scintillator reduces the patient's dose while decreasing the sharpness. A thin scintillator has an advantage in terms of sharpness; however, its noise component increases. Thus, the proposed method converts the spatial resolution of radiographic images acquired from a normal-thickness scintillation detector into a thin-thickness scintillation detector. Note that noise amplification and artifacts were minimized as much as possible after non-blind deconvolution. To accomplish this, the proposed algorithm estimates the optimal point-spread function (PSF) when the structural similarity index (SSIM) and feature similarity index (FSIM) are the most similar between thick and thin scintillator images. Simulation and experimental results demonstrate the viability of the proposed method. Moreover, the deconvolution images obtained using the proposed scheme show an effective image restoration method in terms of the human visible system compared to that of the traditional PSF measurement technique. Consequently, the proposed method is useful for restoring degraded images using the adaptive PSF while preventing noise amplification and artifacts and is effective in improving the image quality in the present X-ray imaging system.

Characterization of Flexible Amorphous Silicon Thin-Film Transistor-Based Detectors with Positive-Intrinsic-Negative Diode in Radiography

Low-dose exposure and work convenience are required for mobile X-ray systems during the COVID-19 pandemic. We investigated a novel X-ray detector (FXRD-4343FAW, VIEWORKS, Anyang, Korea) composed of a thin-film transistor based on amorphous silicon with a flexible plastic substrate. This detector is composed of a thallium-doped cesium iodide scintillator with a pixel size of 99 μm, pixel matrix of 4316 × 4316, and weight of 2.95 kg. The proposed detector has the advantages of high-noise characteristics and low weight, which provide patients and workers with an advantage in terms of the dose and work efficiency, respectively. We performed a quantitative evaluation and an experiment to demonstrate its viability. The modulation transfer function, noise power spectrum, and detective quantum efficiency were identified using the proposed and comparative detectors, according to the International Electrotechnical Commission protocol. Additionally, the contrast-to-noise ratio and coefficient of variation were investigated using a human-like phantom. Our results indicate that the proposed detector efficiently increases the image performance in terms of noise characteristics. The detailed performance evaluation demonstrated that the outcomes of the use of the proposed detector confirmed the viability of mobile X-ray devices that require low doses. Consequently, the novel FXRD-4343FAW X-ray detector is expected to improve the image quality and work convenience in extended radiography.

Effectiveness of Non-Local Means Algorithm with an Industrial 3 MeV LINAC High-Energy X-Ray System for Non-Destructive Testing

Industrial high-energy X-ray imaging systems are widely used for non-destructive testing (NDT) to detect defects in the internal structure of objects. Research on X-ray image noise reduction techniques using image processing has been widely conducted with the aim of improving the detection of defects in objects. In this paper, we propose a non-local means (NLM) denoising algorithm to improve the quality of images obtained using an industrial 3 MeV high-energy X-ray imaging system. We acquired X-ray images using various castings and assessed the performance visually and by obtaining the intensity profile, contrast-to-noise ratio, coefficient of variation, and normalized noise power spectrum. Overall, the quality of images processed by the proposed NLM algorithm is superior to those processed by existing algorithms for the acquired casting images. In conclusion, the NLM denoising algorithm offers an efficient and competitive approach to overcome the noise problem in high-energy X-ray imaging systems, and we expect the accompanying image processing software to facilitate and improve image restoration.

Optimization of Image Quality and Dose in Digital Mammography

Nowadays, the optimization in digital mammography is one of the most important challenges in diagnostic radiology. The new digital technology has introduced additional elements to be considered in this scenario. A major goal of mammography is related to the detection of structures on the order of micrometers (μm) and the need to distinguish the different types of tissues, with very close density values. The diagnosis in mammography faces the difficulty that the breast tissues and pathological findings have very close linear attenuation coefficients within the energy range used in mammography. The aim of this study was to develop a methodology for optimizing exposure parameters of digital mammography based on a new Figure of Merit: FOM ≡ (IQFinv)2/AGD, considering the image quality and dose. The study was conducted using the digital mammography Senographe DS/GE, and CDMAM and TORMAM phantoms. The characterization of clinical practice, carried out in the mammography system under study, was performed considering different breast thicknesses, the technical parameters of exposure, and processing options of images used by the equipment's automatic exposure system. The results showed a difference between the values of the optimized parameters and those ones chosen by the automatic system of the mammography unit, specifically for small breast. The optimized exposure parameters showed better results than those obtained by the automatic system of the mammography, for the image quality parameters and its impact on detection of breast structures when analyzed by radiologists.

Comparison between image quality in electronic zoom and geometric magnification in digital mammography

BACKGROUND

Magnification mammography is performed to enhance the visibility of small structures at the expense of relatively high radiation dose as a complementary examination to standard mammography. The introduction of post-processing capabilities and the widespread use of digital mammography has promoted some controversy in the last decade on whether similar visibility can be achieved using electronic zoom. The aim of this study is to compare the visibility of small structures in images obtained by the two techniques stated above for different exposure conditions.

METHODS

Images of a Fluke Biomedical Model 18-220 Mammography Accreditation Phantom were obtained using standard techniques and geometric magnification, using a digital mammography unit, with different exposure factors. Three different target/filter combinations (Mo/Mo,Mo/Rh,Rh/Rh), variable kVp (26-32), and automatic exposure control were used. Images obtained using standard technique were electronically zoomed and compared to the corresponding magnification mammograms. Comparisons were based on the visibility of structures evaluated by five senior technologist with extensive experience in mammography. Statistical analysis was performed using non-parametric tests.

RESULTS

Visibility of structures was not affected by the kV used for a given target/filter combination for both techniques (p > 0.065). Target/filter combination of Mo/Mo provided better visibility of micro-calcification and fibers (p < 0.026) in geometric magnification technique and Mo/Rh in the digital zoom technique. No significant differences were observed in the visibility of simulated breast masses. The overall image score was significantly higher (p < 0.001) for geometric magnification over the digital zoom for Mo/Mo & Rh/Rh combinations.

CONCLUSION

Although sufficient image quality was maintained in electronically zoomed images, geometric magnification provided better overall visualization of structures in the phantom.

Effects of breast thickness and lesion location on resolution in digital magnification mammography

This study aimed to examine the resolution effects of breast thickness and lesion location in magnification mammography by evaluating generalized modulation transfer function (GMTF) including the effect of focal spot, effective pixel size, and the scatter. Polymethyl methacrylate (PMMA) thicknesses ranging from 10 to 40 mm were placed on a standard supporting platform that was positioned to achieve magnification factors ranging from 1.2 to 2.0. As the magnification increased, the focal spot MTF degraded, while the detector MTF improved. The GMTF depended on the trade-off between the focal spot size and effective pixel size. Breast thickness and lesion location had little effect on the resolution at high frequencies. The resolution of small focal spot did improve slightly with increasing PMMA thickness for magnification factors less than 1.8. In contrast, system resolution decreased with increasing PMMA thickness for magnification factors greater than 1.8 since focal spot blur begins to dominate spatial resolution. In particular, breast thickness had a large effect on the resolution at lower frequencies. A low-frequency drop effect increased with increasing PMMA thickness because of the increase in scatter fraction. Hence, the effect of compressed breast thickness should be considered for the standard magnification factor of 1.8 that is most commonly used in clinical practice. Our results should provide insights for determining optimum magnification in clinical application of digital mammography, and our approaches can be extended to a wide diversity of radiological imaging systems.

Can electronic zoom replace magnification in mammography? A comparative Monte Carlo study

Magnification, which is considered to be a relatively high "dose cost" mammographic technique, is a complementary examination performed on women exhibiting breast complaints or abnormalities. Particular attention is given to the imaging procedure as the primary aim is to confirm the existence of suspected abnormalities, despite the additional dose. The introduction of post-processing capabilities and the widespread use of digital mammography promoted some controversy in the last decades on whether electronic zoom performed on the derived initial screening mammogram can effectively replace this technique. This study used Monte Carlo simulation methods to derive simulated screening mammograms produced under several exposure conditions, aiming to electronically magnify and compare them to the corresponding magnification mammograms. Comparison was based on quantitative measurements of image quality, namely contrast to noise ratio (CNR) and spatial resolution. Results demonstrated that CNR was higher for geometric magnification compared to the case of electronic zooming. The percentage difference was higher for lesions of smaller radius and achieved 29% for 0.10 mm details. Although spatial resolution is maintained high in the zoomed images, when investigating microcalcifications of 0.05 mm radius or less, only with geometric magnification can they be visualised.