• 제목/요약/키워드: Image reconstruction algorithm

검색결과 494건 처리시간 0.029초

DC offset을 보정한 나선 주사 초고속 자기공명영상의 재구성 알고리즘 (Improved Reconstruction Algorithm for Spiral Scan Fast MR Imaging with DC offset Correction)

  • 안창범;김휴정
    • 대한의용생체공학회:의공학회지
    • /
    • 제19권3호
    • /
    • pp.243-250
    • /
    • 1998
  • 초고속 자기공명 영상 기법의 일종인 나선 주사 영상의 재구성을 위하여 k-공간에서 극좌표와 직각 좌표계를 기초로한 재구성방법들을 분석하였다. 나선 주사 영상의 재구성은 나선 궤적상에서 측정된 데이터를 극좌표나 직각 좌표계로 변환시키기 위하여 보간 기술들이 사용된다. 나선주사 영상의 다양한 재구성 알고리즘들을 시험하여 보았고, 재구성된 영상의 질을 비교하였다. 본 연구진이 제안한 투영 영역에서 dc-offset보정을 한 향상된 재구성 알고리즘이 시뮬레이션을 통하여 가장 우수한 것으로 나타났다. 또한, 기존의 재구성 방법들에서 나타났던 영상 artifact도 제안된 방법에서는 완전히 사라짐을 확인할 수 있었다.

  • PDF

조명 조건에 강건한 스마트폰 카메라 맥박 측정을 위한 다이내믹 레인지 재구성 알고리즘 (Dynamic Range Reconstruction Algorithm for Smart Phone Camera Pulse Measurement Robust to Light Condition)

  • 박상욱;차경래
    • 대한임베디드공학회논문지
    • /
    • 제10권1호
    • /
    • pp.1-6
    • /
    • 2015
  • Recently, handy pulse measurement method was introduced by using smart phone camera. However, measured values are not consistent with the variations of external light conditions, because the external light interfere with dynamic range of captured pulse image. Thus, adaptive dynamic range reconstruction algorithm is proposed to conduct pulse measurement robust to light condition. The minimum and maximum values for dynamic ranges of green and blue channels are adjusted to appropriate values for pulse measurement. In addition, sigmoid function based curve is applied to adjusted dynamic range. Experimental results show that the proposed algorithm conducts suitably dynamic range reconstruction of pulse image for the interference of external light sources.

Improvement of Analytic Reconstruction Algorithms Using a Sinogram Interpolation Method for Sparse-angular Sampling with a Photon-counting Detector

  • Kim, Dohyeon;Jo, Byungdu;Park, Su-Jin;Kim, Hyemi;Kim, Hee-Joung
    • 한국의학물리학회지:의학물리
    • /
    • 제27권3호
    • /
    • pp.105-110
    • /
    • 2016
  • Sparse angular sampling has been studied recently owing to its potential to decrease the radiation exposure from computed tomography (CT). In this study, we investigated the analytic reconstruction algorithm in sparse angular sampling using the sinogram interpolation method for improving image quality and computation speed. A prototype of the spectral CT system, which has a 64-pixel Cadmium Zinc Telluride (CZT)-based photon-counting detector, was used. The source-to-detector distance and the source-to-center of rotation distance were 1,200 and 1,015 mm, respectively. Two energy bins (23~33 keV and 34~44 keV) were set to obtain two reconstruction images. We used a PMMA phantom with height and radius of 50.0 mm and 17.5 mm, respectively. The phantom contained iodine, gadolinium, calcification, and lipid. The Feld-kamp-Davis-Kress (FDK) with the sinogram interpolation method and Maximum Likelihood Expectation Maximization (MLEM) algorithm were used to reconstruct the images. We evaluated the signal-to-noise ratio (SNR) of the materials. The SNRs of iodine, calcification, and liquid lipid were increased by 167.03%, 157.93%, and 41.77%, respectively, with the 23~33 keV energy bin using the sinogram interpolation method. The SNRs of iodine, calcification, and liquid state lipid were also increased by 107.01%, 13.58%, and 27.39%, respectively, with the 34~44 keV energy bin using the sinogram interpolation method. Although the FDK algorithm with the sinogram interpolation did not produce better results than the MLEM algorithm, it did result in comparable image quality to that of the MLEM algorithm. We believe that the sinogram interpolation method can be applied in various reconstruction studies using the analytic reconstruction algorithm. Therefore, the sinogram interpolation method can improve the image quality in sparse-angular sampling and be applied to CT applications.

Bayesian Image Reconstruction Using Edge Detecting Process for PET

  • Um, Jong-Seok
    • 한국멀티미디어학회논문지
    • /
    • 제8권12호
    • /
    • pp.1565-1571
    • /
    • 2005
  • Images reconstructed with Maximum-Likelihood Expectation-Maximization (MLEM) algorithm have been observed to have checkerboard effects and have noise artifacts near edges as iterations proceed. To compensate this ill-posed nature, numerous penalized maximum-likelihood methods have been proposed. We suggest a simple algorithm of applying edge detecting process to the MLEM and Bayesian Expectation-Maximization (BEM) to reduce the noise artifacts near edges and remove checkerboard effects. We have shown by simulation that this algorithm removes checkerboard effects and improves the clarity of the reconstructed image and has good properties based on root mean square error (RMS).

  • PDF

스테레오 영상 보정 알고리즘에 기반한 새로운 중간시점 영상합성 기법 (A New Intermediate View Reconstruction Scheme based-on Stereo Image Rectification Algorithm)

  • 박창주;고정환;김은수
    • 한국통신학회논문지
    • /
    • 제29권5C호
    • /
    • pp.632-641
    • /
    • 2004
  • 본 논문에서는 비교정 상태의 스테레오 입력영상에 영상보정 알고리즘을 적용한 새로운 중간시점 영상합성 기법을 제시하고 그 성능을 분석하였다. 제시된 방법에서는 먼저, 좌, 우 스테레오 영상의 각 화소 간들에 대한 유사도 및 모서리 검출을 통해 특징점을 추출한 다음, 이들 특징점을 이용하여 스테레오 영상간의 움직임 벡터와 에피폴라 선을 검출하였다. 그리고 스테레오 영상간의 수평선을 일치시킴으로써 좌, 우 스테레오 영상을 보정하고 최적으로 적응적 변위추정 기법을 이용하여 최적화된 중간시점 영상을 합성하였다. CCETT의 'Man' 영상과 스테레오 카메라를 사용하여 촬영한 '사람' 및 '자동차' 영상을 사용한 중간영상 합성 실험결과 본 논문에서 제안된 보정기법으로 교정된 스테레오 영상의 경우가 비교정 상태에 비해 'Man' 영상은 3.6㏈, '사람' 및 '자동차' 영상은 2.59㏈, 1.47㏈의 PSNR이 각각 개선됨이 분석됨으로써 본 논문에서 새로이 제시한 스테레오 영상 보정 알고리즘 기반의 중간시점 영상합성 기법의 실질적 응용 가능성을 제시하였다.

RECONSTRUCTION OF LIMITED-ANGLE CT IMAGES BY AN ADAPTIVE RESILIENT BACK-PROPAGATION ALGORITHM

  • Kazunori Matsuo;Zensho Nakao;Chen, Yen-Wei;Fath El Alem F. Ah
    • 대한전자공학회:학술대회논문집
    • /
    • 대한전자공학회 2000년도 ITC-CSCC -2
    • /
    • pp.839-842
    • /
    • 2000
  • A new and modified neural network model Is proposed for CT image reconstruction from four projection directions only. The model uses the Resilient Back-Propagation (Rprop) algorithm, which is derived from the original Back-Propagation, for adaptation of its weights. In addition to the error in projection directions of the image being reconstructed, the proposed network makes use of errors in pixels between an image which passed the median filter and the reconstructed one. Improved reconstruction was obtained, and the proposed method was found to be very effective in CT image reconstruction when the given number of projection directions is very limited.

  • PDF

Face Image Compression using Generalized Hebbian Algorithm of Non-Parsed Image

  • Kyung Hwa lee;Seo, Seok-Bae;Kim, Daijin;Kang, Dae-Seong
    • 대한전자공학회:학술대회논문집
    • /
    • 대한전자공학회 2000년도 ITC-CSCC -2
    • /
    • pp.847-850
    • /
    • 2000
  • This paper proposes an image compressing and template matching algorithm for face image using GHA (Generalized Hebbian Algorithm). GHA is a part of PCA (Principal Component Analysis), that has single-layer perceptrons and operates and self-organizing performance. We used this algorithm for feature extraction of face shape, and our simulations verify the high performance for the proposed method. The shape for face in the fact that the eigenvector of face image can be efficiently represented as a coefficient that can be acquired by a set of basis is to compress data of image. From the simulation results, the mean PSNR performance is 24.08[dB] at 0.047bpp, and reconstruction experiment shows that good reconstruction capacity for an image that not joins at leaning.

  • PDF

3D FACE RECONSTRUCTION FROM ROTATIONAL MOTION

  • Sugaya, Yoshiko;Ando, Shingo;Suzuki, Akira;Koike, Hideki
    • 한국방송∙미디어공학회:학술대회논문집
    • /
    • 한국방송공학회 2009년도 IWAIT
    • /
    • pp.714-718
    • /
    • 2009
  • 3D reconstruction of a human face from an image sequence remains an important problem in computer vision. We propose a method, based on a factorization algorithm, that reconstructs a 3D face model from short image sequences exhibiting rotational motion. Factorization algorithms can recover structure and motion simultaneously from one image sequence, but they usually require that all feature points be well tracked. Under rotational motion, however, feature tracking often fails due to occlusion and frame out of features. Additionally, the paucity of images may make feature tracking more difficult or decrease reconstruction accuracy. The proposed 3D reconstruction approach can handle short image sequences exhibiting rotational motion wherein feature points are likely to be missing. We implement the proposal as a reconstruction method; it employs image sequence division and a feature tracking method that uses Active Appearance Models to avoid the failure of feature tracking. Experiments conducted on an image sequence of a human face demonstrate the effectiveness of the proposed method.

  • PDF

Hardware Implementation on the Weight Calculation of Iterative Algorithm for CT Image Reconstruction

  • Cao, Xixin;Ma, Kaisheng;Lian, Renchun;Zhang, Qihui
    • ETRI Journal
    • /
    • 제35권5호
    • /
    • pp.931-934
    • /
    • 2013
  • The weight calculation in an iterative algorithm is the most computationally costly task in computed tomography image reconstruction. In this letter, a fast algorithm to speed up the weight calculation is proposed. The classic square pixel rotation approximate calculation method for computing the weights in the iterative algorithm is first analyzed and then improved by replacing the square pixel model with a circular pixel model and the square rotation approximation with a segmentation method of a circular area. Software simulation and hardware implementation results show that our proposed scheme can not only improve the definition of the reconstructed image but also accelerate the reconstruction.

Development of a novel reconstruction method for two-phase flow CT with improved simulated annealing algorithm

  • Yan, Mingfei;Hu, Huasi;Hu, Guang;Liu, Bin;He, Chao;Yi, Qiang
    • Nuclear Engineering and Technology
    • /
    • 제53권4호
    • /
    • pp.1304-1310
    • /
    • 2021
  • Two-phase flow, especially gas-liquid two-phase flow, has a wide application in industrial field. The diagnosis of two-phase flow parameters, which directly determine the flow and heat transfer characteristics, plays an important role in providing the design reference and ensuring the security of online operation of two-phase flow system. Computer tomography (CT) is a good way to diagnose such parameters with imaging method. This paper has proposed a novel image reconstruction method for thermal neutron CT of two-phase flow with improved simulated annealing (ISA) algorithm, which makes full use of the prior information of two-phase flow and the advantage of stochastic searching algorithm. The reconstruction results demonstrate that its reconstruction accuracy is much higher than that of the reconstruction algorithm based on weighted total difference minimization with soft-threshold filtering (WTDM-STF). The proposed method can also be applied to other types of two-phase flow CT modalities (such as X(𝛄)-ray, capacitance, resistance and ultrasound).