• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2068-2082
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• 2023

With the rapid development of deep learning, Depth Map Super-Resolution (DMSR) method has achieved more advanced performances. However, when the upsampling rate is very large, it is difficult to capture the structural consistency between color features and depth features by these DMSR methods. Therefore, we propose a color-image guided DMSR method based on iterative depth feature enhancement. Considering the feature difference between high-quality color features and low-quality depth features, we propose to decompose the depth features into High-Frequency (HF) and Low-Frequency (LF) components. Due to structural homogeneity of depth HF components and HF color features, only HF color features are used to enhance the depth HF features without using the LF color features. Before the HF and LF depth feature decomposition, the LF component of the previous depth decomposition and the updated HF component are combined together. After decomposing and reorganizing recursively-updated features, we combine all the depth LF features with the final updated depth HF features to obtain the enhanced-depth features. Next, the enhanced-depth features are input into the multistage depth map fusion reconstruction block, in which the cross enhancement module is introduced into the reconstruction block to fully mine the spatial correlation of depth map by interleaving various features between different convolution groups. Experimental results can show that the two objective assessments of root mean square error and mean absolute deviation of the proposed method are superior to those of many latest DMSR methods.

• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.285-295
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• 2023

With the development of technology, efforts to reduce the exposure dose received by patients in CT scans are continuing with the development of new reconstruction techniques. Recently, deep learning reconstruction techniques have been developed to overcome the limitations of repetitive reconstruction techniques. This study aims to evaluate the usefulness of images according to reconstruction techniques in pediatric chest CT images. Patient study conducted a study on 85 pediatric patients who underwent chest CT scan at P-Hospital in Gyeongsangnam-do from January 1, 2021 to December 31, 2022. The phantom used in the Phantom Study is the Pediatrics Whole Body Phantom PBU-70. After the test, the images were reconstructed with FBP, ASIR-V (50%) and DLIR (TF-Medium, High), and the images were evaluated by obtaining SNR and CNR values by setting ROI of the same size. As a result, TF-H of deep learning reconstruction techniques had the lowest noise value compared to ASIR-V (50%) and TF-M in all experiments, and SNR and CNR had the highest values. In pediatric chest CT scans, TF images with deep learning reconstruction techniques were less noisy than ASiR-V images with adaptive statistical iterative reconstruction techniques, CNR and SNR were higher, and the quality of images was improved compared to conventional reconstruction techniques.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3C
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• pp.288-296
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• 2009

In POCS (projection onto convex sets)-based reconstruction of HR (high resolution) image, the quality of reconstructed image is gradually improved through iterative motion estimation and image restoration. The amount of computation, however, increases because of the repeated inter-frame motion estimation. In this paper, an HR reconstruction algorithm is proposed where modified ARPS (adaptive rood pattern search) and POCS are simultaneously performed. In the modified ARPS, the motion estimates obtained from phase correlation or from the previous steps in POCS restoration are utilized as the initial reference in the motion estimation. Moreover, estimated motion is regularized with reference to the neighboring blocks' motion to enhance the reliability. Computer simulation results show that, when compared to conventional methods which are composed of full search block matching and POCS restoration, the proposed method is about 30 times faster and yet produces HR images of almost equal or better quality.

• The Korean Journal of Nuclear Medicine Technology
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• v.18 no.1
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• pp.134-139
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• 2014

Purpose: Adaptive statistical iterative reconstruction (ASIR) technique is a reconstruction method of CT image using statistical noise modeling which is known to reduce image noise and to preserve image quality despite reducing radiation dose. The aim of this study is to evaluate images using ASIR on bone SPECT/CT which is primarily performed in our hospital. Materials and Methods: We compared the images of applied ASIR (ASIR level: 20-80%) and none ASIR by changing the mA based on 120 kVp, 100 mA using Discovery NM/CT 670 (GE, U.S.A). First, we evaluated attenuation correction in SPECT image by changing the ASIR level using Anthropomorphic phantom. Second, we compared the contrast to noise ratio (CNR), image noise and spatial resolution in CT image using ACR phantom. Third, after selecting the ASIR level applicable patient using lower torso phantom, we examined 2 patients who followed up bone SPECT/CT and we performed blind test. Results: The degree of attenuation correction in SPECT image showed no significant difference between applied ASIR and none ASIR (P>0.05). When applied ASIR, the noise of CT image were reduced at least 17 up to 52% by changing the mA. The CNR of image with ASIR was maintained more than 0.8 at 40 mA (ASIR 60%) while those without ASIR showed 0.42 at standard 40 mA. In comparison of the high contrast object, we distinguished 12 line pairs/cm at 40 mA regardless of appling ASIR. Comparison of the patients image applied ASIR level 60% (40 mA) which found out by spine image of lower torso phantom showed no signigicant difference between applied ASIR and none ASIR in blind test. The CTDIvol and DLP for applied ASIR 60% showed decreased by 60%, 60% on average than using standard mA. Conclusion: The study show that the radiation dose in SPECT/CT using ASIR can be reduced despite degradation of SPECT and CT images. In addition, higher ASIR level could be possibly applied characteristics of SPECT/CT that region of interest is limited to bone.

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.1
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• pp.12-16
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• 2012

Purpose : In conventional PET image reconstruction, iterative reconstruction methods such as OSEM (Ordered Subsets Expectation Maximization) have now generally replaced traditional analytic methods such as filtered back-projection. This includes improvements in components of the system model geometry, fully 3D scatter and low noise randoms estimates. SharpIR algorithm is to improve PET image contrast to noise by incorporating information about the PET detector response into the 3D iterative reconstruction algorithm. The aim of this study is evaluation of SharpIR reconstruction method in PET/CT. Materials and Methods: For the measurement of detector response for the spatial resolution, a capillary tube was filled with FDG and scanned at varying distances from the iso-center (5, 10, 15, 20 cm). To measure image quality for contrast recovery, the NEMA IEC body phantom (Data Spectrum Corporation, Hillsborough, NC) with diameters of 1, 13, 17 and 22 for simulating hot and 28 and 37 mm for simulating cold lesions. A solution of 5.4 kBq/mL of $^{18}F$-FDG in water was used as a radioactive background obtaining a lesion of background ratio of 4.0. Images were reconstructed with VUE point HD and VUE point HD using SharpIR reconstruction algorithm. For the clinical evaluation, a whole body FDG scan acquired and to demonstrate contrast recovery, ROIs were drawn on a metabolic hot spot and also on a uniform region of the liver. Images were reconstructed with function of varying iteration number (1~10). Results: The result of increases axial distance from iso-center, full width at half maximum (FWHM) is also increasing in VUE point HD reconstruction image. Even showed an increasing distances constant FWHM. VUE point HD with SharpIR than VUE point HD showed improves contrast recovery in phantom and clinical study. Conclusion: By incorporating more information about the detector system response, the SharpIR algorithm improves the accuracy of underlying model used in VUE point HD. SharpIR algorithm improve spatial resolution for a line source in air, and improves contrast recovery at equivalent noise levels in phantoms and clinical studies. Therefore, SharpIR algorithm can be applied as through a longitudinal study will be useful in clinical.

• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.1
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• pp.9-14
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• 2009

Purpose: Nowadays in the nuclear medicine, many studies and efforts are being made to reduce the scan time, as well as the waiting time to be needed to execute exams after injection of radionuclide medicines. Several methods are being used in clinic, such as developing new radionuclide compounds that enable to be absorbed into target organs more quickly and reducing acquisition scan time by increase the number of Gamma Camera detectors to examine. Each medical equipment manufacturer has improved the imaging process techniques to reduce scan time. In this paper, we tried to analyze the difference of image quality between FBP, 3D OSEM reconstruction methods that commercialized and being clinically applied, and Astonish reconstruction method (A kind of Iterative fast reconstruction method of Philips), also difference of image quality on scan time. Material and Methods: We investigated in 32 patients that examined the Bone SPECT from June to July 2008 at department of nuclear medicine, ASAN Medical Center in Seoul. 40sec/frame and 20sec/frame images were acquired that using Philips‘ PRECEDENCE 16 Gamma Camera and then reconstructed those images by using the Astonish (Philips’ Reconstruction Method), 3D OSEM and FBP methods. The blinded test was performed to the clinical interpreting physicians with all images analyzed by each reconstruction method for qualitative analysis. And we analyzed target to non target ratio by draws lesions as the center of disease for quantitative analysis. At this time, each image was analyzed with same location and size of ROI. Results: In a qualitative analysis, there was no significant difference by acquisition time changes in image quality. In a quantitative analysis, the images reconstructed Astonish method showed good quality due to better sharpness and distinguish sharply between lesions and peripheral lesions. After measuring each mean value and standard deviation value of target to non target ratio with 40 sec/frame and 20sec/frame images, those values are Astonish (40 sec-$13.91{\pm}5.62$ : 20 sec-$13.88{\pm}5.92$), 3D OSEM (40 sec-$10.60{\pm}3.55$ : 20 sec-$10.55{\pm}3.64$), FBP (40 sec-$8.30{\pm}4.44$ : 20 sec-$8.19{\pm}4.20$). We analyzed target to non target ratio from 20 sec and 40 sec images. And we analyzed the result, In Astonish (t=0.16, p=0.872), 3D OSEM (t=0.51, p=0.610), FBP (t=0.73, p=0.469) methods, there was no significant difference statistically by acquisition time change in image quality. But FBP indicates no statistical differences while some images indicate difference between 40 sec/frame and 20 sec/frame images by various factors. Conclusions: In the circumstance, try to find a solution to reduce nuclear medicine scan time, the development of nuclear medicine equipment hardware has decreased while software has marched forward at a relentless. Due to development of computer hardware, the image reconstruction time was reduced and the expanded capacity to restore enables iterative methods that couldn't be performed before due to technical limits. As imaging process technique developed, it reduced scan time and we could observe that image quality keep similar level. While keeping exam quality and reducing scan time can induce the reduction of patient's pain and sensory waiting time, also accessibility of nuclear medicine exam will be improved and it provide better service to patients and clinical physician who order exams. Consequently, those things make the image of department of nuclear medicine be improved. Concurrent Imaging - A new function that setting up each image acquisition parameter and enables to acquire images simultaneously with various parameters to once examine.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.274-277
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• 2013

CT(Computed Tomography)영상에서 선량과 화질은 중요한 요소이다. 선량은 환자에게 직접적으로 악영향을 끼치는 요소이며, 화질은 환자의 병변을 판단하는데 매우 중요하게 작용한다. 반복적 재구성 알고리즘을 이용하면 저선량 영상에서도 고화질의 영상을 얻을 수 있는지 FBP와 정량적, 정성적으로 비교하였다. 촬영 프로토콜은 관전압 80, 100, 120kVp에서 관전류를 동일하게 200mA로 촬영하여 획득하였으며, 정량적 평가를 위해 SD(Standard Deviation), SNR(Signal to Noise Ratio), MTF(Modulation Transfer Function)를 측정하여 분석하였다. 선량은 80kVp일 때 가장 낮았으며, 120kVp일 때 가장 높았다. 80kVp의 영상을 Toshiba 사(社)의 AIDR 3D(Adaptive Iterative Reduction integrated into $^{SURE}Exposure$)로 재구성하고, 120kVp의 영상에 FBP로 재구성한 다음 정량적 비교를 한 결과 AIDR 3D를 적용한 영상의 SD가 낮게 나왔으며, SNR이 높게 나타났고, MTF 곡선은 유사하게 나타났다. 그리고 FWHM(Full Width at Half Maximum) 값의 오차가 거의 없었다. 결론적으로 AIDR 3D는 저선량에서도 높은 화질을 나타냄을 확인하였다.

• Journal of radiological science and technology
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• v.33 no.1
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• pp.31-36
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• 2010

Low energy high resolution (LEHR) collimator is the most widely used collimator in SPECT imaging. LEHR has an advantage in terms of image resolution but has a difficulty in acquiring high sensitivity due to the narrow hole size and long septa height. Throughput in SPECT can be improved by increasing counts per second with the use of high sensitivity collimators. The purpose of this study is to develop a system model in iterative image reconstruction to recover the resolution degradation caused by high sensitivity collimators with bigger hole size. We used fan-beam model instead of parallel-beam model for calculation of detection probabilities to accurately model the high sensitivity collimator with wider holes. In addition the weight factors were calculated and applied onto the probabilities as a function of incident angle of incoming photons and distance from source to the collimator surface. The proposed system model resulted in the equivalent performance with the same counts (i.e. in shortened acquisition time) and improved image quality in the same acquisition time. The proposed method can be effectively applied for resolution improvement of pixel collimator of next generation solid state detectors.

• Korean Journal of Digital Imaging in Medicine
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• v.16 no.2
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• pp.9-14
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• 2014

Purpose: The purpose of this study has attempted to evaluate and compare the image evaluation and exposure dose by respectively applying Filtered Back Projection(FBP), the existing test method, and Adaptive Statistical Iterative Reconstruction(ASIR) with different values of tube voltage during the Low Dose Computed Tomography(LDCT). Materials and Methods: With the image reconstruction method as basis, Chest Phantom was utilized with the FBP and ASIR set at 10%, 20% respectively, and the change of Tube Voltage (100kVp, 120kVp). For image evaluation, Back ground noise, Signal to Noise ratio(SNR) and Contrast to Noise ratio(CNR) were measured, and, for dose evaluation, CTDIvol and DLP were measured respectively. The statistical analysis was tested with SPSS(ver. 22.0), followed by ANOVA Test conducted after normality test and homogeneity test. (p<0.05). Results: In terms of image evaluation, there was no outstanding difference in Ascending Aorta(AA) SNR and Infraspinatus Muscle(IM) SNR with the different values of ASIR application(p<0.05), but a significant difference with the different amount of tube voltage(p>0.05). Also, there wasn't noticeable change in CNR with ASIR and different amount of Tube Voltage (p<0.05). However, in terms of dose evaluation, CTDIvol and DLP showed contrasting results(p<0.05). In terms of CTDIvol, the measured values with the same tube voltage of 120kVp were 2.6mGy with No-ASIR and 2.17mGy with 20%-ASIR respectively, decreased by 0.43mGy, and the values with 100kVp were 1.61mGy with No-ASIR and 1.34mGy with 20%-ASIR, decreased by 0.27mGy. In terms of DLP, the measured values with 120kVp were $103.21mGy{\cdot}cm$ with No-ASIR and $85.94mGy{\cdot}cm$ with 20%-ASIR, decreased by $17.27mGy{\cdot}cm$(about 16.7%), and the values with 100kVp were $63.84mGy{\cdot}cm$ with No-ASIR and $53.25mGy{\cdot}cm$ with 20%-ASIR, a decrease by $10.62mGy{\cdot}cm$(about 16.7%). Conclusion: At lower tube voltage, the rate of dose significantly decreased, but the negative effects on image evaluation was shown due to the increase of noise. For the future, through the result of the experiment, it is considered that the method above would be recommended for follow-up patients or those who get health checkup as long as there is no interference on the process of diagnosis due to the characteristics of Low Dose examination.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2005.11a
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• pp.169-174
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• 2005

In this paper, we proposed a new algorithm of the inverse scattering for the reconstruction of unknown dielectric scatterers using the finite-difference time-domain method and the design sensitivity analysis. We introduced the design sensitivity analysis based on the gradient for the fast convergence of the reconstruction. By introducing the adjoint variable method for the efficient calculation, we derived the adjoint variable equation. As an optimal algorithm we used the steepest descent method and reconstructed the dielectric targets using the iterative estimation. To verify our algorithm we will show the numerical examples for the two-dimensional $TM^2$ cases.