• 제목/요약/키워드: Imaging Processing Technique

검색결과 188건 처리시간 0.029초

2차원 다원주 주위의 유동 특성에 관한 실험적 연구 ( I ) (An Experimental Study of the Flow Characteristics around 2D Multi-Cylinders ( I ))

  • 김두홍;조철희;정우철;박찬원;나인삼
    • 한국해양공학회:학술대회논문집
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    • 한국해양공학회 2001년도 추계학술대회 논문집
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    • pp.190-195
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    • 2001
  • Flow patterns are very complex and interactive between cylinders. The patterns are turbulent and non-linear caused by various factors. In this paper, flow patterns and pressure gradient around vertical cylinders were investigated by experiment. Changing gaps between cylinders the flow patterns are measured at a fixed coming velocity. Flow patterns showed very complex and closely related to the coming velocity and cylinder space. The pressure gradient around the flow field is observed by twelve hole pitot tubes and manometer. The experiment has been conducted in circulating water channel with PIV system. That can visualize flow patterns. The laser beam was used to reflect the image from particles and recorded by CCD camera. The cylinders were spaced from ID to 5D with 0.5m/sec of incoming flow velocity. The experimental results using pitot tube showed in good agreement with results of precious by others study. The results can be applied in the understanding and design of multiple pile array structures.

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Color Enhancement of Low Exposure Images using Histogram Specification and its Application to Color Shift Model-Based Refocusing

  • Lee, Eunsung;Kang, Wonseok;Kim, Sangjin
    • IEIE Transactions on Smart Processing and Computing
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    • 제1권1호
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    • pp.8-16
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    • 2012
  • An image obtained from a low light environment results in a low-exposure problem caused by non-ideal camera settings, i.e. aperture size and shutter speed. Of particular note, the multiple color-filter aperture (MCA) system inherently suffers from low-exposure problems and performance degradation in its image classification and registration processes due to its finite size of the apertures. In this context, this paper presents a novel method for the color enhancement of low-exposure images and its application to color shift model-based MCA system for image refocusing. Although various histogram equalization (HE) approaches have been proposed, they tend to distort the color information of the processed image due to the range limits of the histogram. The proposed color enhancement algorithm enhances the global brightness by analyzing the basic cause of the low-exposure phenomenon, and then compensates for the contrast degradation artifacts by using an adaptive histogram specification. We also apply the proposed algorithm to the preprocessing step of the refocusing technique in the MCA system to enhance the color image. The experimental results confirm that the proposed method can enhance the contrast of any low-exposure color image acquired by a conventional camera, and is suitable for commercial low-cost, high-quality imaging devices, such as consumer-grade camcorders, real-time 3D reconstruction systems, digital, and computational cameras.

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CoReHA: conductivity reconstructor using harmonic algorithms for magnetic resonance electrical impedance tomography (MREIT)

  • Jeon, Ki-Wan;Lee, Chang-Ock;Kim, Hyung-Joong;Woo, Eung-Je;Seo, Jin-Keun
    • 대한의용생체공학회:의공학회지
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    • 제30권4호
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    • pp.279-287
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    • 2009
  • Magnetic resonance electrical impedance tomography (MREIT) is a new medical imaging modality providing cross-sectional images of a conductivity distribution inside an electrically conducting object. MREIT has rapidly progressed in its theory, algorithm and experimental technique and now reached the stage of in vivo animal and human experiments. Conductivity image reconstructions in MREIT require various steps of carefully implemented numerical computations. To facilitate MREIT research, there is a pressing need for an MREIT software package with an efficient user interface. In this paper, we present an example of such a software, called CoReHA which stands for conductivity reconstructor using harmonic algorithms. It offers various computational tools including preprocessing of MREIT data, identification of boundary geometry, electrode modeling, meshing and implementation of the finite element method. Conductivity image reconstruction methods based on the harmonic $B_z$ algorithm are used to produce cross-sectional conductivity images. After summarizing basics of MREIT theory and experimental method, we describe technical details of each data processing task for conductivity image reconstructions. We pay attention to pitfalls and cautions in their numerical implementations. The presented software will be useful to researchers in the field of MREIT for simulation as well as experimental studies.

Common positioning errors in panoramic radiography: A review

  • Rondon, Rafael Henrique Nunes;Pereira, Yamba Carla Lara;do Nascimento, Glauce Crivelaro
    • Imaging Science in Dentistry
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    • 제44권1호
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    • pp.1-6
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    • 2014
  • Professionals performing radiographic examinations are responsible for maintaining optimal image quality for accurate diagnoses. These professionals must competently execute techniques such as film manipulation and processing to minimize patient exposure to radiation. Improper performance by the professional and/or patient may result in a radiographic image of unsatisfactory quality that can also lead to a misdiagnosis and the development of an inadequate treatment plan. Currently, the most commonly performed extraoral examination is panoramic radiography. The invention of panoramic radiography has resulted in improvements in image quality with decreased exposure to radiation and at a low cost. However, this technique requires careful, accurate positioning of the patient's teeth and surrounding maxillofacial bone structure within the focal trough. Therefore, we reviewed the literature for the most common types of positioning errors in panoramic radiography to suggest the correct techniques. We would also discuss how to determine if the most common positioning errors occurred in panoramic radiography, such as in the positioning of the patient's head, tongue, chin, or body.

Gamma correction FCM algorithm with conditional spatial information for image segmentation

  • Liu, Yang;Chen, Haipeng;Shen, Xuanjing;Huang, Yongping
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권9호
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    • pp.4336-4354
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    • 2018
  • Fuzzy C-means (FCM) algorithm is a most usually technique for medical image segmentation. But conventional FCM fails to perform well enough on magnetic resonance imaging (MRI) data with the noise and intensity inhomogeneity (IIH). In the paper, we propose a Gamma correction conditional FCM algorithm with spatial information (GcsFCM) to solve this problem. Firstly, the pre-processing, Gamma correction, is introduced to enhance the details of images. Secondly, the spatial information is introduced to reduce the effect of noise. Then we introduce the effective neighborhood mechanism into the local space information to improve the robustness for the noise and inhomogeneity. And the mechanism describes the degree of participation in generating local membership values and building clusters. Finally, the adjustment mechanism and the spatial information are combined into the weighted membership function. Experimental results on four image volumes with noise and IIH indicate that the proposed GcsFCM algorithm is more effective and robust to noise and IIH than the FCM, sFCM and csFCM algorithms.

Visualization of Crust in Metallic Piping Through Real-Time Neutron Radiography Obtained with Low Intensity Thermal Neutron Flux

  • Luiz, Leandro C.;Ferreira, Francisco J.O.;Crispim, Verginia R.
    • Nuclear Engineering and Technology
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    • 제49권4호
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    • pp.781-786
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    • 2017
  • The presence of crust on the inner walls of metallic ducts impairs transportation because crust completely or partially hinders the passage of fluid to the processing unit and causes damage to equipment connected to the production line. Its localization is crucial. With the development of the electronic imaging system installed at the Argonauta/Nuclear Engineering Institute (IEN)/National Nuclear Energy Commission (CNEN) reactor, it became possible to visualize crust in the interior of metallic piping of small diameter using real-time neutron radiography images obtained with a low neutron flux. The obtained images showed the resistance offered by crust on the passage of water inside the pipe. No discrepancy of the flow profile at the bottom of the pipe, before the crust region, was registered. However, after the passage of liquid through the pipe, images of the disturbances of the flow were clear and discrepancies in the flow profile were steep. This shows that this technique added the assembled apparatus was efficient for the visualization of the crust and of the two-phase flows.

3D 공간상에서의 주변 기울기 정보를 기반에 둔 필터 학습을 통한 MRI 영상 초해상화 (MRI Image Super Resolution through Filter Learning Based on Surrounding Gradient Information in 3D Space)

  • 박성수;김윤수;감진규
    • 한국멀티미디어학회논문지
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    • 제24권2호
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    • pp.178-185
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    • 2021
  • Three-dimensional high-resolution magnetic resonance imaging (MRI) provides fine-level anatomical information for disease diagnosis. However, there is a limitation in obtaining high resolution due to the long scan time for wide spatial coverage. Therefore, in order to obtain a clear high-resolution(HR) image in a wide spatial coverage, a super-resolution technology that converts a low-resolution(LR) MRI image into a high-resolution is required. In this paper, we propose a super-resolution technique through filter learning based on information on the surrounding gradient information in 3D space from 3D MRI images. In the learning step, the gradient features of each voxel are computed through eigen-decomposition from 3D patch. Based on these features, we get the learned filters that minimize the difference of intensity between pairs of LR and HR images for similar features. In test step, the gradient feature of the patch is obtained for each voxel, and the filter is applied by selecting a filter corresponding to the feature closest to it. As a result of learning 100 T1 brain MRI images of HCP which is publicly opened, we showed that the performance improved by up to about 11% compared to the traditional interpolation method.

딥러닝 기법을 이용한 망막 혈관 분할 (Retinal Blood Vessel Segmentation using Deep Learning)

  • 김범상;이익현
    • 한국정보기술학회논문지
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    • 제17권5호
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    • pp.77-82
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    • 2019
  • 당뇨망막증은 망막의 말초혈관에 순환장애가 일어나 발생하는 당뇨병의 합병증으로, 이를 진단하기 위하여 미세혈관류를 분할하였다. 기존 필터와 특징을 사용한 혈관분할은 두꺼운 혈관은 비교적 잘 분할을 하나, 미세한 혈관에 대해서는 정확도가 떨어진다는 단점이 있다. 그리하여 전처리로 노이즈 제거를 위한 필터, 영상 대비를 위한 히스토그램 평활화를 사용하였으며, 픽셀 단위 분할을 위해 딥러닝 기법을 이용하였다. 기존 방법의 정확도는 90% ~ 94%이며, 제안한 방법의 정확도는 95%이다. 결과 영상에서 시신경 유두 및 삼출몰 주변에서 분할 오류가 나타나는 문제점이 있으나, 이는 네트워크 깊이가 얕음에 의한 오류로 향후 네트워크 변경을 통해 정확도를 개선할 수 있다.

Manganese-Enhanced MRI Reveals Brain Circuits Associated with Olfactory Fear Conditioning by Nasal Delivery of Manganese

  • Yang, Ji-ung;Chang, Yongmin;Lee, Taekwan
    • Investigative Magnetic Resonance Imaging
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    • 제26권2호
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    • pp.96-103
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    • 2022
  • Purpose: The survival of organisms critically depends on avoidance responses to life-threatening stimuli. Information about dangerous situations needs to be remembered to produce defensive behavior. To investigate underlying brain regions to process information of danger, manganese-enhanced MRI (MEMRI) was used in olfactory fear-conditioned rats. Materials and Methods: Fear conditioning was conducted in male Sprague-Dawley rats. The animals received nasal injections of manganese chloride solution to monitor brain activation for olfactory information processing. Twenty-four hours after manganese injection, rats were exposed to electric foot shocks with odor cue for one hour. Control rats were exposed to the same odor cue without foot shocks. Forty-eight hours after the conditioning, rats were anesthetized and their brains were scanned with 9.4T MRI. Acquired images were processed and statistical analyses were performed using AFNI. Results: Manganese injection enhanced brain areas involved in olfactory information pathways in T1 weighted images. Rats that received foot shocks showed higher brain activation in the central nucleus of the amygdala, septum, primary motor cortex, and preoptic area. In contrast, control rats displayed greater signals in the orbital cortex and nucleus accumbens. Conclusion: Nasal delivery of manganese solution enhanced olfactory signal pathways in rats. Odor cue paired with foot shocks activated amygdala, the central brain region in fear, and related brain circuits. Use of MEMRI in fear conditioning provides a reliable monitoring technique of brain activation for fear learning.

방출단층촬영 시스템을 위한 GPU 기반 반복적 기댓값 최대화 재구성 알고리즘 연구 (A Study on GPU-based Iterative ML-EM Reconstruction Algorithm for Emission Computed Tomographic Imaging Systems)

  • 하우석;김수미;박민재;이동수;이재성
    • Nuclear Medicine and Molecular Imaging
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    • 제43권5호
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    • pp.459-467
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    • 2009
  • 목적: ML-EM (The maximum likelihood-expectation maximization) 기법은 방출과 검출 과정에 대한 통계학적 모델에 기반한 재구성 알고리즘이다. ML-EM은 결과 영상의 정확성과 유용성에 있어 많은 이점이 있는 반면 반복적인 계산과 방대한 작업량 때문에 CPU(central processing unit)로 처리할 때 상당한 연산시간이 소요되었다. 본 연구에서는 GPU(graphic processing unit)의 병렬 처리 기술을 ML-EM 알고리즘에 적용하여 영상을 재구성하였다. 대상 및 방법: 엔비디아사(社)의 CUDA 기술을 이용하여 ML-EM 알고리즘의 투사 및 역투사 과정을 병렬화 전략을 구상하였으며 Geforce 9800 GTX+ 그래픽 카드를 이용하여 병렬화 연산을 수행하여 기존의 단일 CPU기반 연산법과 비교하였다. 각 반복횟수마다 투사 및 역투사 과정에 걸리는 총 지연 시간과 퍼센트 오차(percent error)를 측정하였다. 총 지연 시간에는 RAM과 GPU 메모리 간의 데이터 전송 지연 시간도 포함하였다. 결과: 모든 반복횟수에 대해 CPU 기반 ML-EM 알고리즘보다 GPU 기반 알고리즘이 더 빠른 성능을 나타내는 것을 확인하였다. 단일 CPU 및 GPU 기반 ML-EM의 32번 반복연산에 있어 각각 3.83초와 0.26초가 걸렸으며 GPU의 병렬연산의 경우 15배 정도의 개선된 성능을 보였다. 반복횟수가 1024까지 증가하였을 경우, CPU와 GPU 기반 알고리즘은 각각 18분과 8초의 연산시간이 걸렸다. GPU 기반 알고리즘이 약 135배 빠른 처리속도를 보였는데 이는 단일 CPU 계산이 특정 반복횟수 이후 나타나는 시간 지연에 따른 것이다. 결과적으로, GPU 기반 계산이 더 작은 편차와 빠른 속도를 보였다. 결론: ML-EM 알고리즘에 기초한 GPU기반 병렬 계산이 처리 속도와 안정성을 더 증진시킴을 확인하였으며 이를 활용해 다른 영상 재구성 알고리즘에도 적용시킬 수 있을 것으로 기대한다.