복부 CT에서 Adaptive Statistical Iterative Reconstruction과 Model-Based Iterative Reconstruction의 사용에 따른 선량 감소 및 화질 평가

손은영(Eun young Son),홍선숙(Sun suk Hong) 대한CT영상기술학회 2013 대한CT영상기술학회지 Vol.15 No.1

목적 본 연구는 복부 CT 검사에서 adaptive statistical iterative reconstruction 기법과 model based iterative reconstruction 기법으로 획득한 이미지를 토대로 복부 장기의 effective dose 변화 및 화질의 정량적인 분석을 통하여 최적의 영상 정보를 제공할 수 있는 iterative reconstruction을 알아보고자 한다. 대상 및 방법 본 연구를 위해 CT 장비는 GE사의 64-slice multidetector-row CT Discovery 750 HD를 사용하였고, 인체 모형 Rando phantom을 사용하였으며, 복부 장기 effective dose 측정을 위하여 유리 선량계를 사용하였다. 장비의 성능 평가를 하기 위하여 ACR phantom을 사용하였고, Image J와 Matlab program을 사용하여 noise, SNR, distortion 및 resolution 측정을 통해 화질을 정량적으로 평가, 분석하였다. 결과 DLP 및 effective dose는 인위적으로 선량을 감소하여 ASIR와 MBIR로 재구성함에 따라 그 비율대로 유사하게 선량이 감소하였다. Noise는 120 mAs-ASIR(ASIR 40%)에서 최소, 100 mAs-ASIR(ASIR 50%)부터 증가하는 것으로 나타났으며, MBIR은 dose를 감소하지 않고 reconstruction하였을 경우 최소로 측정되어 dose가 감소함에 따라 noise는 증가하는 것으로 나타났다. SNR의 경우 180 mAs-ASIR(ASIR 10%)와 140 mAs-MBIR에서 가장 높게 나타났다. 현재 복부 CT에 사용되는 조건의 영상을 기준으로 image의 distortion을 평가했을 때 80 mAs-ASIR(ASIR 70%)까지 PSNR이 30 dB을 넘게 측정되었으며, MBIR은 모두 30 dB 이하로 측정되었다. 해상력과 선예도 측정 결과에서는 100 mAs-MBIR이 100 mAs-ASIR(ASIR 50%)에 비해 sharpness는 20.58%, resolution은 33.19% 높게 측정되었다. ACR phantom을 통한 장비의 성능 평가는 모두 적합한 것으로 나타났다. 결론 본 연구는 복부 CT 검사에서 200 mAs부터 60 mAs까지 10%씩 선량을 감소하여 ASIR와 MBIR로 재구성한 이미지를 토대로 복부 장기의 effective dose 변화 및 화질을 평가하기 위하여 진행하였다. 결과 모두 환자의 선량을 감소시켜 ASIR와 MBIR로 재구성하여도 진단 가치가 있는 것을 확인할 수 있었으며, 이러한 기법을 복부 CT protocol에 적용한 결과 180 mAs-ASIR(ASIR 10%)에서 최적화된 정보를 얻을 수 있었다. MBIR의 경우 ASIR에 비하여 같은 선량에서 약 67%의 많은 noise를 감소하며, 해상력이 높은 것으로 나타났으나 현재 실용화하기 위해서는 고성능의 컴퓨터와 많은 재구성 시간을 요구하는 단점을 가지고 있다. Ⅰ. Purpose The purpose of this study was to assess iterative reconstruction methods that provide optimal image information in abdominal CT exams. It was based on the acquired images by adaptive statistical iterative reconstruction (ASIR) and model- based iterative reconstruction (MBIR). We analyzed the change of effective dose in abdominal organs and image quality quantitatively. Ⅱ. Meterial and Methods CT scans were performed with a 64-slice multidetector-row CT Discovery 750HD and Rando phantom. Glass dosimeters were used to measure effective dose of organs. ACR phantom was used for performance evaluation of the equipment. We quantitatively evaluated and analyzed image quality by measurement of noise, SNR, distortion, and resolution by using Image J and Matlab program. Ⅲ. Result As we gradually lowered radiation dose and reconstructed with ASIR and MBIR, the value of DLP and effective dose also decreased similarly. Noise value was the lowest at 120 mAs-ASIR (ASIR 40%), and got increased from 100 mAs-ASIR (ASIR 50%). SNR value was the highest at 180 mAs-ASIR (ASIR 10%) and 140 mAs-MBIR. In evaluation of distortion of image quality based on abdominal CT protocol, PSNR showed over 30 dB up to 80 mAs-ASIR (ASIR 60%), and below 30 dB at all MBIRs. In measurement of resolution, sharpness and resolving power at 100 mAs-MBIR were respectively 20.58% and 33.19% higher than those at 180 mAs-ASIR (ASIR 10%). All performance evaluation of the equipment through ACR phantom was found to be acceptable. Ⅳ. Conclusions There’s diagnostic value with both iterative reconstruction methods, ASIR and MBIR, while reducing patient dose. In abdominal CT protocol, we can get optimal information at 180 mAs-ASIR (ASIR 10%). MBIR can provide 67% less noise and higher resolution compared to ASIR in the same dose, however, it requires high performance computer and considerable time to reconstruct.

Study on the Super-resolution Reconstruction Algorithm for Remote Sensing Image Based on Compressed Sensing

Qiang Yang,HuaJun Wang,Xuegang Luo 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.6

Image super resolution reconstruction has important significance in remote sensing image feature extraction and classification etc.. Because the remote sensing image size is larger, it is difficult to super resolution reconstruction using multiple images, the compressed sensing (CS) theory was introduced into the super-resolution reconstruction. Algorithm designed the low pass filter to reduce the sample correlation matrix and wavelet, at the same time, the algorithm selects the partial Hadamard-matrix as the measurement matrix, it has faster reconstruction speed and low storage requirements, which ensure that the image reconstruction keep with the RIP criterion of compressed sensing theory . Finally, this paper realizes the remote sensing image super resolution reconstruction through the improved iterative algorithm. Experiments show that the reconstructed images of the PSNR value has increased, the reconstructed image has a better visual effect.

Image Quality and Lesion Detectability of Lower-Dose Abdominopelvic CT Obtained Using Deep Learning Image Reconstruction

Park June,Shin Jaeseung,Min In Kyung,Bae Heejin,Kim Yeo Eun,Chung Yong Eun 대한영상의학회 2022 Korean Journal of Radiology Vol.23 No.4

Objective: To evaluate the image quality and lesion detectability of lower-dose CT (LDCT) of the abdomen and pelvis obtained using a deep learning image reconstruction (DLIR) algorithm compared with those of standard-dose CT (SDCT) images. Materials and Methods: This retrospective study included 123 patients (mean age ± standard deviation, 63 ± 11 years; male:female, 70:53) who underwent contrast-enhanced abdominopelvic LDCT between May and August 2020 and had prior SDCT obtained using the same CT scanner within a year. LDCT images were reconstructed with hybrid iterative reconstruction (h-IR) and DLIR at medium and high strengths (DLIR-M and DLIR-H), while SDCT images were reconstructed with h-IR. For quantitative image quality analysis, image noise, signal-to-noise ratio, and contrast-to-noise ratio were measured in the liver, muscle, and aorta. Among the three different LDCT reconstruction algorithms, the one showing the smallest difference in quantitative parameters from those of SDCT images was selected for qualitative image quality analysis and lesion detectability evaluation. For qualitative analysis, overall image quality, image noise, image sharpness, image texture, and lesion conspicuity were graded using a 5-point scale by two radiologists. Observer performance in focal liver lesion detection was evaluated by comparing the jackknife free-response receiver operating characteristic figures-of-merit (FOM). Results: LDCT (35.1% dose reduction compared with SDCT) images obtained using DLIR-M showed similar quantitative measures to those of SDCT with h-IR images. All qualitative parameters of LDCT with DLIR-M images but image texture were similar to or significantly better than those of SDCT with h-IR images. The lesion detectability on LDCT with DLIR-M images was not significantly different from that of SDCT with h-IR images (reader-averaged FOM, 0.887 vs. 0.874, respectively; p = 0.581). Conclusion: Overall image quality and detectability of focal liver lesions is preserved in contrast-enhanced abdominopelvic LDCT obtained with DLIR-M relative to those in SDCT with h-IR.

연속적인 이미지를 이용한 3차원 장면의 사실적인 복원

전희성 한국정보처리학회 2010 정보처리학회논문지. 소프트웨어 및 데이터 공학 Vol.17 No.3

A factorization-based 3D reconstruction system is realized to recover 3D scene from an image sequence. The image sequence is captured from uncalibrated perspective camera from several views. Many matched feature points over all images are obtained by feature tracking method. Then, these data are supplied to the 3D reconstruction module to obtain the projective reconstruction. Projective reconstruction is converted to Euclidean reconstruction by enforcing several metric constraints. After many triangular meshes are obtained, realistic reconstruction of 3D models are finished by texture mapping. The developed system is implemented in C++, and Qt library is used to implement the system user interface. OpenGL graphics library is used to realize the texture mapping routine and the model visualization program. Experimental results using synthetic and real image data are included to demonstrate the effectiveness of the developed system. 본 연구에서는 여러 이미지를 이용하여 사실적인 3차원 장면의 모델을 얻는 방법이 구현되었다. 이미지는 파라메터를 모르는 카메라를 이용하여 여러 위치에서 획득한 것을 사용하였다. 먼저 특징점 추출 및 추적 방법을 사용하여 모든 이미지에 대한 대응점들을 구하고 이 점들을 사용하여 사영복원을 구한다. 그 다음 사영 복원된 값에 여러 제약조건을 사용하여 유클리디언 복원을 하면 특징점들의 3차원 좌표값이 계산된다. 이 좌표값을 이용하여 삼각형 메쉬를 구한 후 이 면에 텍스처 맵핑을 하면 사실적인 복원이 완성된다. 전체 시스템은 C++언어로 구현하였으며, 사용자 인터페이스는 Qt 라이브러리로, 텍스처 맵핑과 모델 가시화 부분은 OpenGL 그래픽스 라이브러리로 구현하였다. 구현된 시스템의 효용성을 보이기 위해 모의 데이터와 실제 이미지 데이터를 이용하여 실험한 결과를 포함하였으며 만족할 만한 복원 결과를 얻을 수 있었다.

Visual quality enhancement of integral imaging by using pixel rearrangement technique with convolution operator (CPERTS)

Inoue, Kotaro,Cho, Myungjin Elsevier 2018 Optics and lasers in engineering Vol.111 No.-

<P><B>Abstract</B></P> <P>In this paper, we propose a new visual quality enhancement of a three-dimensional (3D) computational reconstruction algorithm in integral imaging. Integral imaging can record 3D images easily using a lenslet array. However, the elemental images may have low resolution, because each image cannot use full resolution of an image sensor. To solve this problem, a computational reconstruction technique can be used to reconstruct visual-quality-enhanced 3D images from low-resolution elemental images. Our method is based on the pixel of elemental images rearrangement technique (PERT), which can provide enhanced visual quality of the reconstructed 3D image compared with that of conventional computational reconstruction algorithms. However, it has a problem in which the size of 3D scenes is different from the optical reconstruction results. Therefore, in this paper, we propose a solution considering empty spaces between back-projected pixels on the reconstruction planes and enhance the extensibility using the convolution operator. Our experimental results show the enhancement of the visual quality and resolution of the reconstructed 3D images using the point-spread function filter.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Captured multi-view images by integral imaging are low-resolution images since image sensors are divided and used by lenslet arrays. </LI> <LI> Conventional 3D reconstruction techniques cannot provide high-resolution 3D images from low-resolution multi-view images. </LI> <LI> Pixel-to-pixel mapping technique can provide accurate pixel positions on reconstruction planes. </LI> <LI> Our proposed method (CPERTS) reconstructs visual quality enhanced 3D images by considering the diffraction pattern of the virtual pinhole using convolution operator. </LI> </UL> </P>

Computational volumetric reconstruction of integral imaging with improved depth resolution considering continuously non-uniform shifting pixels

Cho, Byungwoo,Kopycki, Przemyslaw,Martinez-Corral, Manuel,Cho, Myungjin Elsevier 2018 Optics and lasers in engineering Vol.111 No.-

<P><B>Abstract</B></P> <P>In this paper, we propose a new computational volumetric reconstruction technique of three-dimensional (3D) integral imaging for depth resolution enhancement by using non-uniform and integer-valued shifting pixels. In a typical integral imaging system, 3D images can be recorded and visualized using a lenslet array. In previous studies, many computational reconstruction techniques such as computational volumetric reconstruction and pixel of elemental images rearrangement technique (PERT) have been reported. However, a computational volumetric reconstruction technique has low visual quality and depth resolution because low-resolution elemental images and uniformly distributed shifting pixels are used for reconstruction. Although PERT can enhanced the visual quality of the 3D images, the size of the reconstructed 3D images is different from the original scene. On the other hand, our proposed method uses non-uniformly distributed shifting pixels for reconstruction instead of uniformly distributed shifting pixels. Therefore, the visual quality and depth resolution may be enhanced. Finally, our experimental results show the improvement of depth resolution and visual quality of the reconstructed 3D images.</P> <P><B>Highlights </B></P> <P> <UL> <LI> We present a new reconstruction of integral imaging with integer-valued and non-uniform shifting pixels as shown in Fig. 1. </LI> <LI> However, a conventional computational volumetric reconstruction has high reconstruction error and low depth resolution. </LI> <LI> Furthermore, if the resolution of the elemental images is low, these problems become even bigger. </LI> <LI> We proposed a reconstruction technique to improve depth resolution by using continuously non-uniform shifting pixels. </LI> <LI> Finally, our experimental results as shown in Fig. 2 show the improved depth resolution and reduced reconstruction errors. </LI> </UL> </P>

두 교사의 교육과정 재구성 이미지에 의한 2007 개정초등사회과교육과정 실행양상 해석

한광웅 한국사회교과교육학회 2010 사회과교육연구 Vol.17 No.4

Researcher is described in detail two teacher’s 3, 4 grade social studies instruction applied 2007’s revision primary social studies curriculum and is discovered instruction pattern action revision curriculum by analyzed that content. If Pak teacher is tried soundly representation of revision curriculum at instruction, Choi teacher is seen instruction pattern transform revision curriculum. Pak teacher is constructed three activity by the way of correspondense with a textbook structure. This is closely linked with Pak teacher is tried soundly representation of revision curriculum at instruction. But Choi teacher is acted dual decisionmaking instruction strategy use episode by the way of revision, supplement, and replacement with a textbook content. Researcher is interpreted their instruction pattern by two teacher’s curriculum reconstruction image. Pak teacher’s curriculum reconstruction image, ‘curriculum faithfully perform’ and ‘aim at education content standard’ concur in Pak teacher’s instruction pattern. Choi teacher’s curriculum reconstruction image, ‘spacious reconstruction of curriculum’and ‘numberous change at a textbook content’ discord Pak teacher’s instruction pattern. Choi teacher’s curriculum reconstruction image is vague and blurred so this gap. Teacher’s curriculum reconstruction image is result of teacher’s curriculum understanding. This is constantly base for reasoning Choi teacher’s curriculum reconstruction action. Two teacher’s curriculum reconstruction image is closely met autonomy dilemma hold that understand and action curriculum text. This is the source regularly cut out one’s eyes see curriculum reconstruction. 연구자는 2007 개정 초등사회과교육과정을 올해부터 적용한 두 교사의 3, 4학년 사회과수업을 상세히 기술하고, 이렇게 기술한 내용을 분석하여 개정 교육과정을 실행하는 수업패턴을 발견하였다. 박교사가 수업에서 개정 교육과정의 온전한 재현을 도모하였다면, 최교사는 개정 교육과정을 변용하는 수업패턴을 보였다. 박교사는 교과서 구조와 상호조응하는 방식으로 세 가지 활동을 구성하였다. 이것은 박교사가 개정 교육과정의 온전한 재현을 도모하였다는 점과 밀접히 연동한다. 반면, 최교사는 교과서 내용을 수정, 보완, 대체하는 방식으로 에피소드를 활용한 이중적 의사결정 수업전략을 구안하여 실행하였다. 연구자는 이런 수업패턴을 두 교사의 교육과정 재구성 이미지에 의해 해석하였다. ‘교육과정 충실히 수행하기’와 ‘교육내용의 표준 지향’이라는 박교사의 교육과정 재구성 이미지는 개정 교육과정의 온전한 재현을 도모하는 박교사의 수업패턴과 일치하였다. ‘교육과정의 너른 재구성’과 ‘교과서 내용에 많은 변화주기’라는 최교사의 교육과정 재구성 이미지는 개정 교육과정을 변용하는 최교사의 수업패턴과 불일치하였다. 이런 간극만큼 최교사의 교육과정 재구성 이미지는 모호하고 흐릿하였다. 이런 간극은 최교사가 교육과정 재구성에 의한 실행을 끊임없이 사유하는 기반이었다. 두 교사의 교육과정 재구성 이미지는 교육과정텍스트를 이해하고 실행하면서 갖게 된 자율성 딜레마와 밀접히 맞닿아 있었다. 이것은 두 교사가 교육과정 재구성을 바라보는 시선을 일정하게 재단하는 근원이었다.

Image Quality and Radiation Dose in CT Venography Using Model-Based Iterative Reconstruction at 80 kVp versus Adaptive Statistical Iterative Reconstruction-V at 70 kVp

Chankue Park,Ki Seok Choo,김진혁,Kyung Jin Nam,이지원,김진유 대한영상의학회 2019 Korean Journal of Radiology Vol.20 No.7

Objective: To compare the objective and subjective image quality indicators and radiation doses of computed tomography (CT) venography performed using model-based iterative reconstruction (MBIR) at 80 kVp and adaptive statistical iterative reconstruction (ASIR)-V at 70 kVp. Materials and Methods: Eighty-three patients who had undergone CT venography of the lower extremities with MBIR at 80 kVp (Group A; 21 men and 20 women; mean age, 55.5 years) or ASIR-V at 70 kVp (Group B; 18 men and 24 women; mean age, 57.3 years) were enrolled. Two radiologists retrospectively evaluated the objective (vascular enhancement, image noise, signal-to-noise ratio [SNR], contrast-to-noise ratio [CNR]) and subjective (quantum mottle, delineation of contour, venous enhancement) image quality indicators at the inferior vena cava and femoral and popliteal veins. Clinical information, radiation dose, reconstruction time, and objective and subjective image quality indicators were compared between groups A and B. Results: Vascular enhancement, SNR, and CNR were significantly greater in Group B than in Group A (p ≤ 0.015). Image noise was significantly lower in Group B (p ≤ 0.021), and all subjective image quality indicators, except for delineation of vein contours, were significantly better in Group B (p ≤ 0.021). Mean reconstruction time was significantly shorter in Group B than in Group A (1 min 43 s vs. 131 min 1 s; p < 0.001). Clinical information and radiation dose were not significantly different between the two groups. Conclusion: CT venography using ASIR-V at 70 kVp was better than MBIR at 80 kVp in terms of image quality and reconstruction time at similar radiation doses.

Radiation Dose Reduction of Chest CT with Iterative Reconstruction in Image Space - Part I: Studies on Image Quality Using Dual Source CT

황혜전,서준범,이진성,송재우,김성수,이현주,임채훈 대한영상의학회 2012 Korean Journal of Radiology Vol.13 No.6

Objective: To determine whether the image quality (IQ) is improved with iterative reconstruction in image space (IRIS), and whether IRIS can be used for radiation reduction in chest CT. Materials and Methods: Standard dose chest CT (SDCT) in 50 patients and low dose chest CT (LDCT) in another 50 patients were performed, using a dual-source CT, with 120 kVp and same reference mAs (50 mAs for SDCT and 25 mAs for LDCT) employed to both tubes by modifying a dual-energy scan mode. Full-dose data were obtained by combining the data from both tubes and half-dose data were separated from a single tube. These were reconstructed by using a filtered back projection (FBP) and IRIS: full-dose FBP (F-FBP); full-dose IRIS (F-IRIS); half-dose FBP (H-FBP) and half-dose IRIS (H-IRIS). Objective noise was measured. The subjective IQ was evaluated by radiologists for the followings: noise, contrast and sharpness of mediastinum and lung. Results: Objective noise was significantly lower in H-IRIS than in F-FBP (p < 0.01). In both SDCT and LDCT, the IQ scores were highest in F-IRIS, followed by F-FBP, H-IRIS and H-FBP, except those for sharpness of mediastinum, which tended to be higher in FBP. When comparing CT images between the same dose and different reconstruction (F-IRIS/F-FBP and H-IRIS/H-FBP) algorithms, scores tended to be higher in IRIS than in FBP, being more distinct in half-dose images. However, despite the use of IRIS, the scores were lower in H-IRIS than in F-FBP. Conclusion: IRIS generally helps improve the IQ, being more distinct at the reduced radiation. However, reduced radiation by half results in IQ decrease even when using IRIS in chest CT. Objective: To determine whether the image quality (IQ) is improved with iterative reconstruction in image space (IRIS), and whether IRIS can be used for radiation reduction in chest CT. Materials and Methods: Standard dose chest CT (SDCT) in 50 patients and low dose chest CT (LDCT) in another 50 patients were performed, using a dual-source CT, with 120 kVp and same reference mAs (50 mAs for SDCT and 25 mAs for LDCT) employed to both tubes by modifying a dual-energy scan mode. Full-dose data were obtained by combining the data from both tubes and half-dose data were separated from a single tube. These were reconstructed by using a filtered back projection (FBP) and IRIS: full-dose FBP (F-FBP); full-dose IRIS (F-IRIS); half-dose FBP (H-FBP) and half-dose IRIS (H-IRIS). Objective noise was measured. The subjective IQ was evaluated by radiologists for the followings: noise, contrast and sharpness of mediastinum and lung. Results: Objective noise was significantly lower in H-IRIS than in F-FBP (p < 0.01). In both SDCT and LDCT, the IQ scores were highest in F-IRIS, followed by F-FBP, H-IRIS and H-FBP, except those for sharpness of mediastinum, which tended to be higher in FBP. When comparing CT images between the same dose and different reconstruction (F-IRIS/F-FBP and H-IRIS/H-FBP) algorithms, scores tended to be higher in IRIS than in FBP, being more distinct in half-dose images. However, despite the use of IRIS, the scores were lower in H-IRIS than in F-FBP. Conclusion: IRIS generally helps improve the IQ, being more distinct at the reduced radiation. However, reduced radiation by half results in IQ decrease even when using IRIS in chest CT.

Development of image reconstruction algorithm with iterative method using maximum-likelihood expectation-maximization (MLEM) for chest digital tomosynthesis (CDT) X-ray system

Lee, S.,Kang, S.H.,Heo, Y.C.,Lee, Y. Wissenschaftliche Verlagsgesellschaft m. b. H 2017 OPTIK -STUTTGART- Vol.150 No.-

<P>Digital tomosynthesis system (DTS) has been increasingly used in chest X-ray imaging with a limited-projection angle image reconstruction method. Image reconstruction methods in chest digital tomosynthesis (CDT) have fundamental impacts on image characteristics. Among these methods, iterative algorithm provides the additional benefits of chest X-ray imaging. However, there is almost no research that maximum-likelihood expectation-maximization (MLEM) method in CDT system. Thus, the purpose of this study was (1) to develop MLEM reconstruction algorithm based on CDT system and (2) to quantitatively compare the image characteristics with respect to the total angular range and iteration number as applied this system. For that purpose, we performed both simulation using MATLAB program and experimental studies. Tomography was performed linearly with a maximum +/- 30 degrees total angular range and then we acquired Shepp-Logan and PMMA-Aluminum (Al) phantom images using 120 kVp X-ray source for simulation and experiment, respectively. We evaluated and compared the MLEM reconstructed image characteristics using root-mean-square error (RMSE) and signal difference-to-noise ratio (SDNR) with various total angular ranges and iteration numbers. According to the results, we can acquire improved image characteristics as the number of iterations and the number of projections increased. Also, we found optimized iteration number for 20 iteration numbers in our CDT system geometry because there were few changes of image characteristics over 20 iteration numbers. In conclusion, we have presented usefulness and effectiveness of developed CDT image reconstruction algorithm. (C) 2017 Elsevier GmbH. All rights reserved.</P>