• Title/Summary/Keyword: Image-guided

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Feasibility of MFC (Macro-Fiber Composite) Transducers for Guided Wave Technique

  • Ren, Gang;Yun, Dongseok;Seo, Hogeon;Song, Minkyoo;Jhang, Kyung-Young
    • Journal of the Korean Society for Nondestructive Testing
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    • v.33 no.3
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    • pp.264-269
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    • 2013
  • Since MFC(macro-fiber composite) transducer has been developed, many researchers have tried to apply this transducer on SHM(structural health monitoring), because it is so flexible and durable that it can be easily embedded to various kinds of structures. The objective of this paper is to figure out the benefits and feasibility of applying MFC transducers to guided wave technique. For this, we have experimentally tested the performance of MFC patches as transmitter and sensors for excitation and reception of guided waves on the thin aluminum alloy plate. In order to enhance the signal accuracy, we applied the FIR filter for noise reduction as well as used STFT(short-time Fourier transform) algorithm to image the guided wave characteristics clearly. From the results, the guided wave generated based on MFC showed good agreement with its theoretical dispersion curves. Moreover, the ultrasonic Lamb wave techniques based on MFC patches in pitch-catch manner was tested for detection of surface notch defects of which depths are 10%, 20%, 30% and 40% of the aluminum plate thickness. Results showed that the notch was detectable well when the notch depth was 10% of the thickness or greater.

Hybrid Tone Mapping Technique Considering Contrast and Texture Area Information for HDR Image Restoration (HDR 영상 복원을 위해 대비와 텍스쳐 영역 정보를 고려한 혼합 톤 매핑 기법)

  • Kang, Ju-Mi;Park, Dae-Jun;Jeong, Jechang
    • Journal of Broadcast Engineering
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    • v.22 no.4
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    • pp.496-508
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    • 2017
  • In this paper, we propose a Tone Mapping Operator (TMO) that preserves global contrast and precisely preserves boundary information. In order to reconstruct a High Dynamic Range (HDR) image to a Low Dynamic Range (LDR) display by using Threshold value vs. Intensity value (TVI) based on Human Visual System (HVS) and contrast value. As a result, the global contrast of the image can be preserved. In addition, by combining the boundary information detected using Guided Image Filtering (GIF) and the detected boundary information using the spatial masking of the Just Noticeable Difference (JND) model, And improved the perceived image quality of the output image. The conventional TMOs are classified into Global Tone Mapping (GTM) and Local Tone Mapping (LTM). GTM preserves global contrast, has the advantages of simple implementation and fast execution time, but it has a disadvantage in that the boundary information of the image is lost and the regional contrast is not preserved. On the other hand, the LTM preserves the local contrast and boundary information of the image well, but some areas are expressed unnatural like the occurrence of the halo artifact phenomenon in the boundary region, and the calculation complexity is higher than that of GTM. In this paper, we propose TMO which preserves global contrast and combines the merits of GTM and LTM to preserve boundary information of images. Experimental results show that the proposed tone mapping technique has superior performance in terms of cognitive quality.

Multiparametric MRI in Active Surveillance of Prostate Cancer: An Overview and a Practical Approach

  • Chau Hung Lee;Teck Wei Tan;Cher Heng Tan
    • Korean Journal of Radiology
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    • v.22 no.7
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    • pp.1087-1099
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    • 2021
  • MRI has become important for the detection of prostate cancer. MRI-guided biopsy is superior to conventional systematic biopsy in patients suspected with prostate cancer. MRI is also increasingly used for monitoring patients with low-risk prostate cancer during active surveillance. It improves patient selection for active surveillance at diagnosis, although its role during follow-up is unclear. We aim to review existing evidence and propose a practical approach for incorporating MRI into active surveillance protocols.

Image Reconstruction Using Poisson Model Screened from Image Gradient (이미지 기울기에서 선별된 포아송 모델을 이용한 이미지 재구성)

  • Kim, Yong-Gil
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.2
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    • pp.117-123
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    • 2018
  • In this study, we suggest a fast image reconstruction scheme using Poisson equation from image gradient domain. In this approach, using the Poisson equation, a guided vector field is created by employing source and target images within a selected region at the first step. Next, the guided vector is used in generating the result image. We analyze the problem of reconstructing a two-dimensional function that approximates a set of desired gradients and a data term. The joined data and gradients are able to work like modifying the image gradients while staying close to the original image. Starting with this formulation, we have a screened Poisson equation known in physics. This equation leads to an efficient solution to the problem in FFT domain. It represents the spatial filters that solve the two-dimensional screened Poisson model and shows gradient scaling to be a well-defined sharpen filter that generalizes Laplace sharpening. We demonstrate the results using a discrete cosine transformation based this Poisson model.

A Multi Resolution Based Guided Filter Using Fuzzy Logic for X-Ray Medical Images (방사선 의료영상 잡음제거를 위한 퍼지논리 활용 다해상도 기반 유도필터)

  • Ko, Seung-Hyun;Pant, Suresh Raj;Lee, Joonwhoan
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.4
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    • pp.372-378
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    • 2014
  • Noise in biomedical X-ray image degrades the quality so that it might causes to decrease the accuracy of diagnosis. Especially the noise reduction techniques is quite essential for low-dose biomedical X-ray images obtained from low radiation power in order to protect patients, because their noise level is usually high to well discriminate objects. This paper proposes an efficient method to remove the noise in low-dose X-ray images while preserving the edges with diverse resolutions. In the proposed method, a noisy image is at first decomposed into several images with different resolutions in pyramidal representation, then the stable map of edge confidence is obtained from each of analyzed image using a fuzzy logic-based edge detector. This map is used to adaptively determine the parameter for guided filters, which eliminate the noise while preserving edges in the corresponding image. The filtered images in the pyramid are extended and synthesized into a resulted image using interpolation technique. The superiority of proposed method compared to the median, bilateral, and guided filters has been experimentally shown in terms of noise removal and edge preserving properties.

Modified Adaptive Logarithmic Mapping Method using Guided Image Filter (가이디드 이미지 필터를 이용한 향상된 적응적 로그 매핑 기법)

  • Yoon, Hakyung;Wee, Seungwoo;Jeong, Jechang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2017.11a
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    • pp.88-91
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    • 2017
  • 넓은 동적 영역 (high dynamic range: HDR) 이미지는 시각적으로 우수하지만 대부분의 디스플레이는 좁은 동적 영역 (low dynamic range: LDR)만 지원이 가능하다. 이를 해결하기 위해서 톤 매핑 기법 (tone mapping operator: TMO)을 사용한 동적 영역 압축을 수행한다. 기존의 적응적 로그 매핑 (adaptive logarithmic mapping)의 경우 에지 부분에서 디테일이 손실되는 문제점이 있었다. 본 논문에서는 가이디드 이미지 필터링 (guided image filtering: GIF)을 통해 베이스 레이어와 디테일 레이어로 나눠서 처리하는 알고리듬을 제안한다. 베이스 레이어는 적응적 로그 매핑을 통해 동적 영역을 압축하고 디테일 레이어와 더해 기존의 톤 매핑 과정에서 발생하는 디테일의 손실을 감소시켰다.

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A Tone Mapping Algorithm Based on Multi-scale Decomposition

  • Li, Weizhong;Yi, Benshun;Huang, Taiqi;Yao, Weiqing;Peng, Hong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.4
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    • pp.1846-1863
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    • 2016
  • High dynamic range (HDR) images can present the perfect real scene and rich color information. A commonly encountered problem in practical applications is how to well visualize HDR images on standard display devices. In this paper, we propose a multi-scale decomposition method using guided filtering for HDR image tone mapping. In our algorithm, HDR images are directly decomposed into three layers:base layer, coarse scale detail layer and fine detail layer. We propose an effective function to compress the base layer and the coarse scale detail layer. An adaptive function is also proposed for detail adjustment. Experimental results show that the proposed algorithm effectively accomplishes dynamic range compression and maintains good global contrast as well as local contrast. It also presents more image details and keeps high color saturation.

Kalman Filter Baded Pose Data Fusion with Optical Traking System and Inertial Navigation System Networks for Image Guided Surgery (영상유도수술을 위한 광학추적 센서 및 관성항법 센서 네트웍의 칼만필터 기반 자세정보 융합)

  • Oh, Hyun Min;Kim, Min Young
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.1
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    • pp.121-126
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    • 2017
  • Tracking system is essential for Image Guided Surgery(IGS). Optical Tracking System(OTS) is widely used to IGS for its high accuracy and easy usage. However, OTS doesn't work when occlusion of marker occurs. In this paper sensor data fusion with OTS and Inertial Navigation System(INS) is proposed to solve this problem. The proposed system improves the accuracy of tracking system by eliminating gaussian error of the sensor and supplements the disadvantages of OTS and IMU through sensor fusion based on Kalman filter. Also, sensor calibration method that improves the accuracy is introduced. The performed experiment verifies the effectualness of the proposed algorithm.

Histogram Equalization Algorithm for Suppressing Over-Enhancement and Enhancing Edges (과대 대조 강조 방지 및 엣지 강화를 동시에 수행하는 히스토그램 평활화 알고리듬)

  • Mun, Junwon;Kim, Jaeseok
    • Journal of Korea Multimedia Society
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    • v.22 no.9
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    • pp.983-991
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    • 2019
  • Histogram equalization method is a popular contrast enhancement technique. However, there are some drawbacks, namely, over-enhancement, under-enhancement, structure information loss, and noise amplification. In this paper, we propose an edge-enhancing histogram equalization algorithm while suppressing over-enhancement simultaneously. Firstly, over-enhancement is suppressed by clipping a transfer function, then, edge enhancement is achieved by using guided image filter. Experiments are carried out to evaluate the performance of the various HE algorithms. As a result, both qualitative and quantitative assessment showed that the proposed algorithm successfully suppressed over-enhancement while enhancing edges.

Backlit Region Detection Using Adaptively Partitioned Block and Fuzzy C-means Clustering for Backlit Image Enhancement (역광 영상 개선을 위한 퍼지 C-평균 분류기와 적응적 블록 분할을 사용한 역광 영역 검출)

  • Kim, Nahyun;Lee, Seungwon;Paik, Joonki
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.2
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    • pp.124-132
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    • 2014
  • In this paper, we present a novel backlit region detection and contrast enhancement method using fuzzy C-means clustering and adaptively partitioned block based contrast stretching. The proposed method separates an image into both dark backlit and bright background regions using adaptively partitioned blocks based on the optimal threshold value computed by fuzzy logic. The detected block-wise backlit region is refined using the guided filter for removing block artifacts. Contrast stretching algorithm is then applied to adaptively enhance the detected backlit region. Experimental results show that the proposed method can successfully detect the backlit region without a complicated segmentation algorithm and enhance the object information in the backlit region.