KEYWORDS: Denoising, Modulation transfer functions, Spatial resolution, Mammography, Image quality, Digital mammography, Monte Carlo methods, Image processing
With an increase of breast cancer patients, dual-energy mammographic techniques have been advanced for improving diagnostic accuracy. In general, conventional dual-energy techniques increase radiation dose because the techniques are based on double exposures. Dual-energy techniques with photon-counting detectors (PCDs) can be implemented by using a single exposure. However, the images obtained from the dual-energy techniques with the PCDs suffer from statistical noise because the dual-energy measurements were performed with a single exposure, causing a lack of the number of effective photons. Thus, the material decomposition accuracy is decreased, and the image quality is distorted. In this study, denoising and deblurring techniques were iteratively applied to a dual-energy mammographic technique based on a PCD, and we evaluated RMSE, noise, and CNR for the quantitative analysis of material decomposition. The results showed that the RMSE value was about 0.23 times lower for the decomposed images with the denoising and deblurring techniques than that without the denoising and deblurring techniques. The noise and CNR of the decomposed images were averagely decreased and increased by factors of 0.23 and 4.17, respectively, through the denoising and deblurring techniques. But, the iterative application of the debelurring technique slightly increased the RMSE and noise. Therefore, it is considered that the material decomposition accuracy and image quality can be improved by applying the denoising and deblurring techniques with the appropriate iterations.
Digital tomosynthesis (DT) improves the diagnostic accuracy compared with 2D radiography due to the good depth resolution. In addition, the DT can reduce radiation dose by more than 80% compared to computed tomography (CT) owing to the scans with limited angles. However, the conventional DT systems have the disadvantages such as geometric complexity and low efficiency. Moreover, the movements of source and detector cause motion artifacts in reconstructed images. Therefore, with the stationary X-ray source and detector, it is possible to reduce the artifacts by simplifying the geometry while preserving the advantages of DT imaging. Also, the geometric inversion with a small detector allows the more efficient diagnosis because fields-of-view (FOVs) can be smaller than the conventional DT systems. The purpose of this study was to develop the stationary inverse-geometry digital tomosynthesis (s-IGDT) imaging technique and compare image quality for linear and curved X-ray source arrays. The signal-to-noise ratio (SNR) of s-IGDT images obtained by using the linear X-ray source array was averagely 1.84 times higher than that using the curved X-ray source array due to low noise components, but the root-mean-square error (RMSE) was averagely 3.25 times higher. The modulation-transfer function (MTF) and radiation dose of the s-IGDT systems with the linear and curved X-ray source arrays were measured at similar levels. As a result, the s-IGDT system with the linear X-ray source array is superior in terms of SNR and noise property, and the curved X-ray array system is superior in terms of quantitative accuracy.
KEYWORDS: Lung, Xenon, Chronic obstructive pulmonary disease, X-rays, Polymethylmethacrylate, Pulmonary function tests, Monte Carlo methods, Sensors, Signal attenuation, X-ray imaging
Due to various factors, the number of chronic obstructive pulmonary disease (COPD) patients continues to increase. In addition, the mortality from COPD is increasing because of the difficult in the early detection of COPD. Radiologic and respiratory examinations should be performed simultaneously for improving the diagnostic accuracy of COPD. But a conventional respiratory examination leads to diagnostic inaccuracy and decreases the reproducibility of examinations because there is air leakage between spirometry and mouth. Also, it is difficult to apply for all ages. In this study, we confirmed the possibility of material decomposition for pulmonary function test by combining dual-energy X-ray images obtained from a photon counting detector. Non-radioactive Xe, which appears in X-ray images, was also used. The RMSE of each material in decomposed images was analyzed to quantitatively evaluate of the possibility of material decomposition for pulmonary function test. Results showed that the average RMSE values of PMMA, lung and nonradioactive Xe were 0.005, 0.0199 and 0.0217, respectively, and we observed the high accuracy of material decomposition. Therefore, the diagnosis of COPD can be simplified through the material decomposition imaging using non-radiologic Xe, and the lung function can be evaluated by decomposing the total lung and actual gas exchange areas.
With the advent of the coherent age the implementation of massive digital signal processors (DSP) co-integrated with high speed AD and DA converters became feasible allowing for the realization of huge flexibility of transponders. Today the implementation of variable transponders is mainly based on variable programming of DSP to support different modulation formats and symbol rates. Modulation formats with high flexibility are required such as pragmatic QAM formats and hybrid modulation formats. Furthermore, we report on an implementable probabilistically shaping technique allowing for adjusting the bitrate. We introduce fundamental characteristics of all modes and describe basic operation principles. The modifications of the operational modes are enabled simply by switching between different formats and symbol rates in the DSP to adjust the transponders spectral efficiency, the bitrate and the maximum transmission distance. A fine granularity in bitrate and in maximum transmission distance can be implemented especially by hybrid formats and by probabilistically shaped formats. Furthermore, latter allow for ~+25% increase of the maximum transmission distance due their operation close to the Shannon limit as a consequence of their 2D Gaussian like signal nature. If the flexibility and programmability of transponders is implemented, it can be utilized to support different strategies for the application. The variability in symbol rate is mainly translated into variability in bitrate and in bandwidth consumption. Contrary the variable spectral efficiency translates into a variation of the maximum transmission reach and of the bitrate. A co-adjustment of both options will lead to a superior flexibility of optical transponders to address all requirements from application, transponder and fiber infrastructure perspective.
Recently, image-guided radiation therapy (IGRT) with cone-beam computed tomography (CBCT) has been used to precisely identify the location of target lesion. However, the treatment accuracy for respiratory-sensitive regions is still low, and the imaging dose is also relatively high. These issues can be solved by using the respiratory-correlated 4D IGRT with digital tomosynthesis (DT). The purpose of this study was to develop the 4D DT imaging technique for the IGRT and compare image quality between the 3D DT and 4D DT. A DT model was based on a linear accelerator (LINAC) system. In order to simulate the motion of a lesion the sphere defined in a 3D phantom was moved with an irregular pattern. Projections were separately obtained through 3 phases, which were sorted according to the position of the sphere, for simulating the 4D DT imaging. We measured profile, normalized root-mean-square error (NRMSE), noise, contrast-to-noise ratio (CNR) and figure-of-merit (FOM). Noise of 4D DT images was averagely 0.99 times lower than 3D DT images. And, NRMSEs, CNRs, and FOMs of 4D DT images were averagely 1.03, 1.22, and 4.48 times higher than those of 3D DT images, respectively. The results showed that the 4D DT imaging technique accurately determined the position of a moving target and improved image quality compared to the 3D DT imaging technique. These benefits will enable the high-precision IGRT for respiratory-sensitive regions.
Contrast-enhanced mammography has been used to demonstrate functional information about a breast tumor by injecting
contrast agents. However, a conventional technique with a single exposure degrades the efficiency of tumor detection
due to structure overlapping. Dual-energy techniques with energy-integrating detectors (EIDs) also cause an increase of
radiation dose and an inaccuracy of material decomposition due to the limitations of EIDs. On the other hands, spectral
mammography with photon-counting detectors (PCDs) is able to resolve the issues induced by the conventional
technique and EIDs using their energy-discrimination capabilities. In this study, the contrast-enhanced spectral
mammography based on a PCD was implemented by using a polychromatic dual-energy model, and the proposed
technique was compared with the dual-energy technique with an EID in terms of quantitative accuracy and radiation
dose. The results showed that the proposed technique improved the quantitative accuracy as well as reduced radiation
dose comparing to the dual-energy technique with an EID. The quantitative accuracy of the contrast-enhanced spectral
mammography based on a PCD was slightly improved as a function of radiation dose. Therefore, the contrast-enhanced
spectral mammography based on a PCD is able to provide useful information for detecting breast tumors and improving
diagnostic accuracy.
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