A Novel Multimodal Image Fusion Method Using Hybrid Wavelet-based Contourlet Transform

Various image fusion techniques have been studied to meet the requirements of different applications such as concealed weapon detection, remote sensing, urban mapping, surveillance and medical imaging. Combining two or more images of the same scene or object produces a better application-wise visible image. The conventional wavelet transform (WT) has been widely used in the field of image fusion due to its advantages, including multi-scale framework and capability of isolating discontinuities at object edges. However, the contourlet transform (CT) has been recently adopted and applied to the image fusion process to overcome the drawbacks of WT with its own advantages. Based on the experimental studies in this dissertation, it is proven that the contourlet transform is more suitable than the conventional wavelet transform in performing the image fusion. However, it is important to know that the contourlet transform also has major drawbacks. First, the contourlet transform framework does not provide shift-invariance and structural information of the source images that are necessary to enhance the fusion performance. Second, unwanted artifacts are produced during the image decomposition process via contourlet transform framework, which are caused by setting some transform coefficients to zero for nonlinear approximation. In this dissertation, a novel fusion method using hybrid wavelet-based contourlet transform (HWCT) is proposed to overcome the drawbacks of both conventional wavelet and contourlet transforms, and enhance the fusion performance. In the proposed method, Daubechies Complex Wavelet Transform (DCxWT) is employed to provide both shift-invariance and structural information, and Hybrid Directional Filter Bank (HDFB) is used to achieve less artifacts and more directional information. DCxWT provides shift-invariance which is desired during the fusion process to avoid mis-registration problem. Without the shift-invariance, source images are mis-registered and non-aligned to each other; therefore, the fusion results are significantly degraded. DCxWT also provides structural information through its imaginary part of wavelet coefficients; hence, it is possible to preserve more relevant information during the fusion process and this gives better representation of the fused image. Moreover, HDFB is applied to the fusion framework where the source images are decomposed to provide abundant directional information, less complexity, and reduced artifacts. The proposed method is applied to five different categories of the multimodal image fusion, and experimental study is conducted to evaluate the performance of the proposed method in each multimodal fusion category using suitable quality metrics. Various datasets, fusion algorithms, pre-processing techniques and quality metrics are used for each fusion category. From every experimental study and analysis in each fusion category, the proposed method produced better fusion results than the conventional wavelet and contourlet transforms; therefore, its usefulness as a fusion method has been validated and its high performance has been verified

Blood Pressure and the Risk of Death From Non-cardiovascular Diseases: A Population-based Cohort Study of Korean Adults

Objectives The objective of this study was to assess the relationship between systolic and diastolic blood pressure (SBP, DBP) and the risk of death from specific causes other than cardiovascular diseases. Methods We calculated the risk of specific death by SBP and DBP categories for 506 508 health examinees in 2002-2003 using hazard ratios (HRs) and 95% confidence intervals (CIs) in a Cox proportional hazards model. Results Compared to normal levels (SBP <120 or DBP <90 mmHg), stage I systolic and diastolic hypertension (SBP 140-159, DBP 85- 89 mmHg, respectively) were associated with an increased risk of death from diabetes mellitus, alcoholic liver disease, and renal failure (HR, 1.83; 95% CI, 1.51 to 2.22; HR, 1.24; 95% CI, 1.06 to 1.46; HR, 2.30; 95% CI, 1.64 to 3.21; HR, 1.67; 95% CI, 1.27 to 2.20; HR, 1.99; 95% CI, 1.41 to 2.81; HR, 1.31; 95% CI, 0.99 to 1.73, respectively), but a decreased risk of death from intestinal pneumonia (HR, 0.64; 95% CI, 0.42 to 0.98; HR, 0.59; 95% CI, 0.39 to 0.91). Only stage II systolic hypertension (SBP ≥160 mmHg) was associated with an increased risk of death from pneumonia, liver cirrhosis, and intestinal ischemia (HR, 1.54; 95% CI, 1.19 to 1.98; HR, 1.46; 95% CI, 1.00 to 2.15; HR, 3.77; 95% CI, 1.24 to 11.40, respectively), and stage I and II diastolic hypertension (SBP 140-159 and ≥160 mmHg) were associated with an increased risk of death from intestinal ischemia (HR, 3.07; 95% CI, 1.27 to 7.38; HR, 4.39; 95% CI, 1.62 to 11.88, respectively). Conclusions An increase in blood pressure levels may alter the risk of death from certain causes other than cardiovascular diseases, a well-known outcome of hypertension, although the mechanism of these associations is not well documented

Vaccine effectiveness and the epidemiological characteristics of a COVID-19 outbreak in a tertiary hospital in Republic of Korea

Objectives Healthcare facilities are high-risk sites for infection. This study analyzed the epidemiological characteristics of a coronavirus disease 2019 (COVID-19) outbreak in a tertiary hospital after COVID-19 vaccination had been introduced in Republic of Korea. Vaccine effectiveness (VE) and shared anti-infection strategies are also assessed. Methods The risk levels for 4,074 contacts were evaluated. The epidemiological characteristics of confirmed cases were evaluated using the chi-square test. The “1 minus relative risk” method was used to determine VE in preventing infection, progression to severe disease, and death. In the largest affected area (the 8th floor), a separate relative risk analysis was conducted. A multivariate logistic regression analysis (with 95% confidence interval [CIs]) was used to identify transmission risk factors with a significance level <10% via the backward elimination method. Results In total, 181 cases of COVID-19 were confirmed, with an attack rate of 4.4%. Of those cases, 12.7% progressed to severe disease, and 8.3% died. In the cohort isolation area on the 8th floor, where 79.0% of the confirmed cases occurred, the adjusted odds ratio was 6.55 (95% CI, 2.99–14.33) and 2.19 (95% CI, 1.24–3.88) for caregivers and the unvaccinated group, respectively. VE analysis revealed that 85.8% of the cases that progressed to severe disease and 78.6% of the deaths could be prevented by administering a second vaccine. Conclusion Caregiver training for infection prevention and control is necessary to reduce infection risk. Vaccination is an important intervention to reduce the risk of progression to severe disease and death

Development of brain PET using GAPD arrays

Purpose: In recent times, there has been great interest in the use of Geiger-mode avalanche photodiodes (GAPDs) as scintillator readout in positron emission tomography (PET) detectors because of their advantages, such as high gain, compact size, low power consumption, and magnetic field insensitivity. The purpose of this study was to develop a novel PET system based on GAPD arrays for brain imaging. Methods: The PET consisted of 72 detector modules arranged in a ring of 330 mm diameter. Each PET module was composed of a 4 Â 4 matrix of 3 Â 3 Â 20 mm 3 cerium-doped lutetium yttrium orthosilicate (LYSO) crystals coupled with a 4 Â 4 array three-side tileable GAPD. The signals from each PET module were fed into preamplifiers using a 3 m long flat cable and then sent to a position decoder circuit (PDC), which output a digital address and an analog pulse of the interacted channel among 64 preamplifier signals tranmitted from four PET detector modules. The PDC outputs were fed into field programmable gate array (FPGA)-embedded data acquisition (DAQ) boards. The analog signal was then digitized, and arrival time and energy of the signal were calculated and stored. Results: The energy and coincidence timing resolutions measured for 511 keV gamma rays were 18.4 6 3.1% and 2.6 ns, respectively. The transaxial spatial resolution and sensitivity in the center of field of view (FOV) were 3.1 mm and 0.32% cps/Bq, respectively. The rods down to a diameter of 2.5 mm were resolved in a hot-rod phantom image, and activity distribution patterns between the white and gray matters in the Hoffman brain phantom were well imaged. Conclusions: Experimental results indicate that a PET system can be developed using GAPD arrays and the GAPD-based PET system can provide high-quality PET imaging

A Feasibility Study for Diagnosis of Latent Tuberculosis Infection Using an IGRA Point-of-Care Platform in South Korea.

PURPOSE: This study aimed to evaluate ichroma™ IGRA-TB, a novel point-of-care platform for assaying IFN-γ release, and to compare it with QuantiFERON-TB Gold In-Tube (QFT-GIT) for identifying Mycobacterium tuberculosis (M. tb) infection. MATERIALS AND METHODS: We recruited 60 healthy subjects, and blood samples were obtained in QFT-GIT blood collection tubes. The blood collection tubes were incubated at 37°C, and culture supernatant was harvested after 18-24 hours. IFN-γ responses were assessed by the ichroma™ IGRA-TB cartridge and the QFT-GIT IFN-γ enzyme-linked immunosorbent assay. Three active TB patients were recruited as a positive control for M. tb infection. RESULTS: The area under the receiver operating characteristic curve of the ichroma™ IGRA-TB test for differentiating between infected and non-infected individuals was 0.9706 (p<0.001). Inconsistent positivity between the two tests was found in three participants who showed weak positive IFN-γ responses (<1.0 IU/mL) with QFT-GIT. However, the two tests had excellent agreement (95.2%, κ=0.91, p<0.001), and a very strong positive correlation was observed between the IFN-γ values of both tests (r=0.91, p<0.001). CONCLUSION: The diagnostic accuracy demonstrated in this study indicates that the ichroma™ IGRA-TB test could be used as a rapid diagnostic method for detecting latent TB infection. It may be particularly beneficial in resource-limited places that require cost-effective laboratory diagnostics

A Simulation Study of Target Detection Using Hyperspectral Data Analysis

Target detection is difficult when the target is concealed or placed under ground or water. To detect and identify concealed objects from a distance, the analysis of the HyperSpectral Imaging (HSI) and Wideband (WB) data is studied. While the HSI analysis may render surface information about objects, the WB data can reveal information about inner layers of the object and its content. Two of the challenging issues with object identification using HSI are (i) computational complexity of the analysis and (ii) signature mismatch. Here, the robust matched filter is emphasized for HSI processing. In addition, the wideband technology is utilized to provide more information about concealed target, and to support spectral processing for object uncovering more effectively. During simulation, electromagnetic waves and propagation areas are modeled. In fact, an object is modeled as different layers with different thicknesses. The existence of a target is estimated by the detection of spectral signatures relating to materials used in the target. In other words, the simultaneous presence of spectral signatures corresponding to the main materials of the target in the hyperspectral data helps detecting the target. The reflected higher frequency signals provide information about exterior layers of both an object and the background; in addition, the reflected lower frequency signals provide information about interior layers of the object. To identify different objects, the simulation is performed using HSI, and WB technology at different frequencies (MHz- GHz) and powers. Based on simulation, the proposed method can be a promising approach to detect targets

A Variable-Sampling Time Model Predictive Control Algorithm for Improving Path-Tracking Performance of a Vehicle

This paper proposes a novel model predictive control (MPC) algorithm that increases the path tracking performance according to the control input. The proposed algorithm reduces the path tracking errors of MPC by updating the sampling time of the next step according to the control inputs (i.e., the lateral velocity and front steering angle) calculated in each step of the MPC algorithm. The scenarios of a mixture of straight and curved driving paths were constructed, and the optimal control input was calculated in each step. In the experiment, a scenario was created with the Automated Driving Toolbox of MATLAB, and the path-following performance characteristics and computation times of the existing and proposed MPC algorithms were verified and compared with simulations. The results prove that the proposed MPC algorithm has improved path-following performance compared to those of the existing MPC algorithm

Okounkov bodies associated to pseudoeffective divisors

An Okounkov body is a convex subset in Euclidean space associated to a big divisor on a smooth projective variety with respect to an admissible flag. In this paper, we introduce two convex bodies associated to pseudoeffective divisors, called the valuative Okounkov bodies and the limiting Okounkov bodies, and show that these convex bodies reflect the asymptotic properties of pseudoeffective divisors as in the case with big divisors. Our results extend the works of Lazarsfeld–Mustat¸˘a and Kaveh–Khovanskii. For this purpose, we define and study special subvarieties, called the Nakayama subvarieties and the positive volume subvarieties, associated to pseudoeffective divisors.C.2018 London Mathematical Societ