• 제목/요약/키워드: Registration Correction

검색결과 67건 처리시간 0.033초

REGISTRATION OF MICROSCOPIC SECTION IMAGES BASED ON A RADIAL DISTORTION MODEL

  • Lee, Hoo-Sung;Yun, Il-Dong;Kim, Dong-Sik
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2009년도 IWAIT
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    • pp.303-306
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    • 2009
  • Registration of microscopic section images from an organism is of importance in analyzing and understanding the function of an organism. Microscopes usually suffer from the radial distortion due to the spherical aberration. In this paper, a correction scheme for the intra-section registration is proposed. The correction scheme uses two corresponding feature points under the radial distortion model. Proposing several variations of the proposed scheme, we extensively conducted experiments for real microscopic images. Iterative versions of the correction from multiple feature points provide good performance for the registration of the optical and scanning electron microscopic images.

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Z-correction, a new method to improve TFT mask set overlay for TFT production yield enhancement

  • Ekberg, Peter;Sjostrom, Fredrik;Stiblert, Lars
    • 한국정보디스플레이학회:학술대회논문집
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    • 한국정보디스플레이학회 2005년도 International Meeting on Information Displayvol.I
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    • pp.598-601
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    • 2005
  • Z-correction is new method to be used when measuring pattern registration of photomasks. The method is based on measurement of the plate profile in the Zaxis and takes into account the impact on the registration deviations caused by plate support, contamination as well as the photomask flatness itself. Z-correction further facilitates a more neutral way of judging the overlay properties between individual photomasks within a mask set.

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Respiratory Motion Correction on PET Images Based on 3D Convolutional Neural Network

  • Hou, Yibo;He, Jianfeng;She, Bo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권7호
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    • pp.2191-2208
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    • 2022
  • Motion blur in PET (Positron emission tomography) images induced by respiratory motion will reduce the quality of imaging. Although exiting methods have positive performance for respiratory motion correction in medical practice, there are still many aspects that can be improved. In this paper, an improved 3D unsupervised framework, Res-Voxel based on U-Net network was proposed for the motion correction. The Res-Voxel with multiple residual structure may improve the ability of predicting deformation field, and use a smaller convolution kernel to reduce the parameters of the model and decrease the amount of computation required. The proposed is tested on the simulated PET imaging data and the clinical data. Experimental results demonstrate that the proposed achieved Dice indices 93.81%, 81.75% and 75.10% on the simulated geometric phantom data, voxel phantom data and the clinical data respectively. It is demonstrated that the proposed method can improve the registration and correction performance of PET image.

PET/CT 영상 움직임 보정 (Motion Correction in PET/CT Images)

  • 우상근;천기정
    • Nuclear Medicine and Molecular Imaging
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    • 제42권2호
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    • pp.172-180
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    • 2008
  • PET/CT fused image with anatomical and functional information have improved medical diagnosis and interpretation. This fusion has resulted in more precise localization and characterization of sites of radio-tracer uptake. However, a motion during whole-body imaging has been recognized as a source of image quality degradation and reduced the quantitative accuracy of PET/CT study. The respiratory motion problem is more challenging in combined PET/CT imaging. In combined PET/CT, CT is used to localize tumors and to correct for attenuation in the PET images. An accurate spatial registration of PET and CT image sets is a prerequisite for accurate diagnosis and SUV measurement. Correcting for the spatial mismatch caused by motion represents a particular challenge for the requisite registration accuracy as a result of differences in PET/CT image. This paper provides a brief summary of the materials and methods involved in multiple investigations of the correction for respiratory motion in PET/CT imaging, with the goal of improving image quality and quantitative accuracy.

유리함수모델 기반 표고시차보상기법을 사용한 Image Registration 방안 제안 (The Suggestion of the Image Registration Using Terrain Relief Correction Based on RFM)

  • 김현숙;김문규;서두천
    • 한국측량학회지
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    • 제30권1호
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    • pp.21-30
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    • 2012
  • 위성 카메라의 두 밴드가 다른 관측 각(Look angle)으로 촬영 시, 두 밴드간의 정합이 요구된다. 밴드 정합(Band registration)은 플랫폼의 다이나믹스(Dynamics)와 시차효과로 인하여 상수매개변수(constant parameter)로 수학적인 모델을 수립하여 정합(registration)을 수행하기 어렵다. 시차효과는 지표면 표고에 의해 야기되는 현상으로 이는 두 밴드간 정합 특성이 지표면의 표고의 함수로 주어진다. 두 밴드간 정합이 성공적으로 이뤄지기 위하여 시차효과를 보상하는 표고시차보상기법이 요구된다. 이러한 표고시차보상은 특히 고해상도 영상정합에서 중요하다. 표고시차보상기법은 하나의 밴드를 다른 관측 각을 가지는 다수의 CCD라인으로 구성한 경우에도 적용이 가능하다. 한 밴드에서 촬영된CCD라인 영상들은 연결된CCD라인마다 다른 관측 각을 가짐으로CCD라인간 표고시차가 발생하여 CCD라인간 지상거리 차가 표고에 따라 증가되는 왜곡 현상이 나타나기 때문이다. 이를 보상하기 위해 기준밴드 또는 기준 CCD라인과 대상밴드 또는 대상 CCD라인간 영상과 지상간의 관계를 다항식을 사용하여 수학적으로 모델 하는RFM을 사용하였다. 실험결과, 표고시차가 존재하는 영상에 대해서도 제안된 기법으로 밴드 정합이 성공적으로 수행되는 것을 확인하였다.

Scene-based Nonuniformity Correction Complemented by Block Reweighting and Global Offset Initialization

  • Hong, Yong-hee;Lee, Keun-Jae;Kim, Hong-Rak;Jhee, Ho-Jin
    • 한국컴퓨터정보학회논문지
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    • 제22권8호
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    • pp.15-23
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    • 2017
  • In this paper, the block reweighting and global offset initialization methods are proposed to complement the improved IRLMS algorithm which is the effective algorithm in registration based SBNUC algorithm. Proposed block weighting method reweights the error map whose abnormal data are excluded. The global offset initialization method compensates the global nonuniformity initially. The ordinary registration based SBNUC algorithm is hard to compensate global nonuniformity because of low scene motion. We employ the proposed methods to improved IRLMS algorithm, and apply it to real-world infrared raw image stream. The result shows that new implementation provides 3.5~4.0dB higher PSNR and convergence speed 1.5 faster then the improved IRLMS algorithm.

영상보정 및 다단계 정합을 통한 전립선 MR 영상과 병리 영상간 융합 (Prostate MR and Pathology Image Fusion through Image Correction and Multi-stage Registration)

  • 정주립;조현희;홍헬렌
    • 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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    • 제15권9호
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    • pp.700-704
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    • 2009
  • 본 논문은 영상보정 및 다단계 정합을 통한 전립선의 MR 영상과 병리 영상 간의 융합방법을 제안한다. 제안 방법은 영상보정, 강체 정합, 비강체 정합, 영상융합의 네 단계로 이루어진다. 첫째, 영상보정 단계에서 T2 MR 강조 영상의 출혈 부위의 자기값을 T1 MR 강조 영상의 자기값으로 대체시키고, 2, 4장으로 분리된 병리 영상을 한장의 영상으로 만든 후 MR 영상과 동일한 해상도로 줄인다. 둘째, 전립선의 T2 MR 강조 영상과 병리 영상 간에 자기간의 상호정보를 최적화하는 강체변환을 구한다. 셋째, TPS 와핑을 이용하여 병리 영상의 전립선 부위가 T2 MR 강조 영상의 전립선 부위에 정합되는 비강체변환을 구한다. 넷째, MR 영상과 변환을 적용시킨 병리 영상을 융합한다. 실험 결과 영상보정 및 다단계 정합 후의 전립선의 T2 MR 강조 영상과 병리 영상의 간의 평균 거리 오차는 0.8815 mm였고, 두 영상의 융합을 통해 T2 MR 강조 영상에서 전립선 암의 위치를 정확하게 볼 수 있었다.

AUTOMATIC PRECISION CORRECTION OF SATELLITE IMAGES

  • Im, Yong-Jo;Kim, Tae-Jung
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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    • pp.40-44
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    • 2002
  • Precision correction is the process of geometrically aligning images to a reference coordinate system using GCPs(Ground Control Points). Many applications of remote sensing data, such as change detection, mapping and environmental monitoring, rely on the accuracy of precision correction. However it is a very time consuming and laborious process. It requires GCP collection, the identification of image points and their corresponding reference coordinates. At typical satellite ground stations, GCP collection requires most of man-powers in processing satellite images. A method of automatic registration of satellite images is demanding. In this paper, we propose a new algorithm for automatic precision correction by GCP chips and RANSAC(Random Sample Consensus). The algorithm is divided into two major steps. The first one is the automated generation of ground control points. An automated stereo matching based on normalized cross correlation will be used. We have improved the accuracy of stereo matching by determining the size and shape of match windows according to incidence angle and scene orientation from ancillary data. The second one is the robust estimation of mapping function from control points. We used the RANSAC algorithm for this step and effectively removed the outliers of matching results. We carried out experiments with SPOT images over three test sites which were taken at different time and look-angle with each other. Left image was used to select UP chipsets and right image to match against GCP chipsets and perform automatic registration. In result, we could show that our approach of automated matching and robust estimation worked well for automated registration.

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A STUDY ON THE GENERATION OF EO STANDARD IMAGE PRODUCTS: SPOT

  • JUNG HYUNG-SUP;KANG MYUNG-HO;LEE YONG-WOONG;LEE HO-NAM;WON JOONG-SUN
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.216-219
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    • 2004
  • In this study, the concept and techniques to generate the level lA, lB and 2A image products have been reviewed. In particular, radiometric and geometric corrections and bands registration used to generate level lA, lB and 2A products have been focused in this study. Radiometric correction is performed to take into account radiometric gain and offset calculated by compensating the detector response non-uniformity. And, in order to compensate satellite altitude, attitude, skew effects, earth rotation and earth curvature, some geometric parameters for geometric corrections are computed and applied. Bands registration process using the matching function between a geometry, which is called 'reference geometry', and another one which is corresponds to the image to be registered is applied to images in case of multi-spectral imaging mode. In order to generate level-lA image products, a simple radiometric processing is applied to a level-0 image. Level-lB image has the same radiometry correction as a level-lA image, but is also issued from some geometric corrections in order to compensate skew effects, Earth rotation effects and spectral misregistration. Level-2A image is generated using some geo-referencing parameters computed by ephemeris data, orbit attitudes and sensor angles. Level lA image is tested by visual analysis. The difference between distances calculated level 1 B image and distances of real coordinate is tested. Level 2A image is tested Using checking points.

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혈관조영영상에서 고화질 혈관가시화를 위한 영상정합 (Image Registration for High-Quality Vessel Visualization in Angiography)

  • 홍헬렌;이호;신영길
    • 한국시뮬레이션학회:학술대회논문집
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    • 한국시뮬레이션학회 2003년도 추계학술대회 및 정기총회
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    • pp.201-206
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    • 2003
  • In clinical practice, CT Angiography is a powerful technique for the visualziation of blood flow in arterial vessels throughout the body. However CT Angiography images of blood vessels anywhere in the body may be fuzzy if the patient moves during the exam. In this paper, we propose a novel technique for removing global motion artifacts in the 3D space. The proposed methods are based on the two key ideas as follows. First, the method involves the extraction of a set of feature points by using a 3D edge detection technique based on image gradient of the mask volume where enhanced vessels cannot be expected to appear, Second, the corresponding set of feature points in the contrast volume are determined by correlation-based registration. The proposed method has been successfully applied to pre- and post-contrast CTA brain dataset. Since the registration for motion correction estimates correlation between feature points extracted from skull area in mask and contrast volume, it offers an accelerated technique to accurately visualize blood vessels of the brain.

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