• 제목/요약/키워드: Gray Region

검색결과 333건 처리시간 0.032초

VGG-based BAPL Score Classification of 18F-Florbetaben Amyloid Brain PET

  • Kang, Hyeon;Kim, Woong-Gon;Yang, Gyung-Seung;Kim, Hyun-Woo;Jeong, Ji-Eun;Yoon, Hyun-Jin;Cho, Kook;Jeong, Young-Jin;Kang, Do-Young
    • 대한의생명과학회지
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    • 제24권4호
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    • pp.418-425
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    • 2018
  • Amyloid brain positron emission tomography (PET) images are visually and subjectively analyzed by the physician with a lot of time and effort to determine the ${\beta}$-Amyloid ($A{\beta}$) deposition. We designed a convolutional neural network (CNN) model that predicts the $A{\beta}$-positive and $A{\beta}$-negative status. We performed 18F-florbetaben (FBB) brain PET on controls and patients (n=176) with mild cognitive impairment and Alzheimer's Disease (AD). We classified brain PET images visually as per the on the brain amyloid plaque load score. We designed the visual geometry group (VGG16) model for the visual assessment of slice-based samples. To evaluate only the gray matter and not the white matter, gray matter masking (GMM) was applied to the slice-based standard samples. All the performance metrics were higher with GMM than without GMM (accuracy 92.39 vs. 89.60, sensitivity 87.93 vs. 85.76, and specificity 98.94 vs. 95.32). For the patient-based standard, all the performance metrics were almost the same (accuracy 89.78 vs. 89.21), lower (sensitivity 93.97 vs. 99.14), and higher (specificity 81.67 vs. 70.00). The area under curve with the VGG16 model that observed the gray matter region only was slightly higher than the model that observed the whole brain for both slice-based and patient-based decision processes. Amyloid brain PET images can be appropriately analyzed using the CNN model for predicting the $A{\beta}$-positive and $A{\beta}$-negative status.

담양(潭陽)-진안(鎭安)사이에 분포(分布)하는 엽리상화강암류(葉理狀花崗岩類)에 대(對)한 지질시대(地質時代)와 성인(成因)에 관(關)한 연구(硏究) (Geochronology and Petrochemistry of Foliated Granites between Damyang and Jinan)

  • 김정빈;김용준
    • 자원환경지질
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    • 제23권2호
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    • pp.233-244
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    • 1990
  • Plutons of Damyang-Jinan area consist of gray feldspar granite gneiss, biotite granite gneiss, foliated granites, Namweon granites, gabbro, biotite granite and Ogangri granite in term of mineralogical, texture and field evidence. From Isotope data of study area, chronological order of the Plutons are the Pre-cambrian gray feldspar granite gneiss(Ar39-Ar40, hornblende, $1998.4{\pm}8.3Ma$), middle to late Triassic Daegang foliated granite(Rb/Sr, whole rock, $288{\pm}4Ma$), foliated hornblende biotite granodiorite(K/Ar, hornblende, $198.7{\pm}9.9Ma$), Sunchang foliated granodiorite(Rb/Sr, whole rock, $222{\pm}4Ma$), foliated two mica granite, Samori foliated granite and Namweon granite(Rb/Sr, whole rock, $211{\pm}3Ma$: K/Ar, hornblende, $203{\pm}10.2Ma$), middle Jurassic Gabbro(K/Ar, hornblende, $180.7{\pm}9MA$) and biotite granite, and Cretaceous Ogangri granite. According to variations diagrams of $Al_2O_3$ versus normative PI(100 An)/(Ab+An), Daegang foliated granite is plotted on tholeiitic series, and other foliated granites on calc alkaline rock series which are consider to be formed by magmatism at continental margin and island arc region. And alkalinity versus $SiO_2$ shows that Daegang folited granite and Samori foliated granite are correspond to alkaline region, foliated hornblende biotite granodiorite and Sunchang foliated granodiorite to calc alkaline region, and foliated two mica granite to both regions. According to ACF diagrams, Daegang and Samori foliated granites are plotted on S-type. Foliated hornblende biotite granodiorite and Sunchang foliated granodiorite on I-type, and foliated two mica granite on both type. Foliated granites are a series of differentiated products from cogenetic magma, and effected under ductile sheared zone. Characteristic foliation of foliated granites are considered to be generated by dextral strike slip faulting and ductile shearing.

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An image enhancement Method for extracting multi-license plate region

  • Yun, Jong-Ho;Choi, Myung-Ryul;Lee, Sang-Sun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권6호
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    • pp.3188-3207
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    • 2017
  • In this paper, we propose an image enhancement algorithm to improve license plate extraction rate in various environments (Day Street, Night Street, Underground parking lot, etc.). The proposed algorithm is composed of image enhancement algorithm and license plate extraction algorithm. The image enhancement method can improve an image quality of the degraded image, which utilizes a histogram information and overall gray level distribution of an image. The proposed algorithm employs an interpolated probability distribution value (PDV) in order to control a sudden change in image brightness. Probability distribution value can be calculated using cumulative distribution function (CDF) and probability density function (PDF) of the captured image, whose values are achieved by brightness distribution of the captured image. Also, by adjusting the image enhancement factor of each part region based on image pixel information, it provides a function that can adjust the gradation of the image in more details. This processed gray image is converted into a binary image, which fuses narrow breaks and long thin gulfs, eliminates small holes, and fills gaps in the contour by using morphology operations. Then license plate region is detected based on aspect ratio and license plate size of the bound box drawn on connected license plate areas. The images have been captured by using a video camera or a personal image recorder installed in front of the cars. The captured images have included several license plates on multilane roads. Simulation has been executed using OpenCV and MATLAB. The results show that the extraction success rate is more improved than the conventional algorithms.

의료 영상을 이용한 인체 역학적 구조물 특징 추출 및 영상 분할 (Feature Extraction and Image Segmentation of Mechanical Structures from Human Medical Images)

  • 호동수;김성현;김도일;서태석;최보영;김의녕;이진희;이형구
    • 한국의학물리학회지:의학물리
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    • 제15권2호
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    • pp.112-119
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    • 2004
  • 인체에 대한 표준데이터를 사용하지 않고 실제 한국인의 의료 영상 데이터를 사용하여 인체 모델을 만들고자 하였다. 먼저 CT와 MRI를 통해 획득한 인체의 의료영상에 대한 특징을 분석하였다. 인체의 해부학적인 구성요소에 대해 CT는 gray level로 MR 영상은 펄스시퀀스 별로 분석하여 특징을 추출하였다. 해부학적 구성요소의 특징을 바탕으로 인체 각 부위별로 영상을 얻기 위해 CT와 MR 영상에 대해 영상분할을 수행하였다. 인체의 부위 중 특히 인체의 네 가지 인체 역학적 구조물인 골조직, 근육, 인대, 건 부위를 CT와 MR 영상을 이용하여 구별하였다. 이미지 분할 방법에는 일반적으로 많이 사용되고 있는 경계선 검출(Edge detection), 영역 선택(Region Growing), 문턱치(Intensity Threshold) 방법 등을 선택하여 인체별로 가장 적합한 알고리듬을 적용시켰다. Head/Neck 부위에 대한 영상 분할 결과를 인체 역학적 구성요소별로 3차원 영상으로 재구성하였다.

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국소 영역별 대비 개선과 쌍선형 보간에 의한 불균등 대비 영상의 효율적 적응 이진화 (An Adaptive Thresholding of the Nonuniformly Contrasted Images by Using Local Contrast Enhancement and Bilinear Interpolation)

  • 정동현;조상현;최흥문
    • 전자공학회논문지S
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    • 제36S권12호
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    • pp.51-57
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    • 1999
  • 본 논문에서는 불균등 대비 영상에서 국소 영역별 대비개선과 문턱치 평면의 쌍선형 보간을 이용한 효과적인 적응 이진화 방법을 제안하였다. 제안한 방법에서는 먼저 영상을 국소 영역으로 나누고, 영역별로 흐리거나 대비가 낮은 부분의 명도차를 증대시켜 전체적으로 대비를 개선한 후, 대비 개선된 국소 영역별 명도 분포로부터 해당 영역의 최적 문턱치를 구하였다. 국소 영역간에 이웃하는 문턱치들을 쌍선형 보간하여 전역적으로 영역별 문턱치들간의 불연속성을 없앰으로써 불균등 대비 영상에 대해서도 관심 영역이나 문자 부분에서의 불연속을 줄이도록 하였다. 불균등 대비를 갖는 일반문서 및 PCB나 웨이퍼상의 문자 영상을 제안한 방법과 기존 방법으로 이진화한 영상들로부터 문자들을 추출하고, 동일 조건하에서 같은 역전파 신경회로망으로 인식 실험하여 제안한 방법의 실효성을 확인하였다.

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Iris Image Enhancement for the Recognition of Non-ideal Iris Images

  • Sajjad, Mazhar;Ahn, Chang-Won;Jung, Jin-Woo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권4호
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    • pp.1904-1926
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    • 2016
  • Iris recognition for biometric personnel identification has gained much interest owing to the increasing concern with security today. The image quality plays a major role in the performance of iris recognition systems. When capturing an iris image under uncontrolled conditions and dealing with non-cooperative people, the chance of getting non-ideal images is very high owing to poor focus, off-angle, noise, motion blur, occlusion of eyelashes and eyelids, and wearing glasses. In order to improve the accuracy of iris recognition while dealing with non-ideal iris images, we propose a novel algorithm that improves the quality of degraded iris images. First, the iris image is localized properly to obtain accurate iris boundary detection, and then the iris image is normalized to obtain a fixed size. Second, the valid region (iris region) is extracted from the segmented iris image to obtain only the iris region. Third, to get a well-distributed texture image, bilinear interpolation is used on the segmented valid iris gray image. Using contrast-limited adaptive histogram equalization (CLAHE) enhances the low contrast of the resulting interpolated image. The results of CLAHE are further improved by stretching the maximum and minimum values to 0-255 by using histogram-stretching technique. The gray texture information is extracted by 1D Gabor filters while the Hamming distance technique is chosen as a metric for recognition. The NICE-II training dataset taken from UBRIS.v2 was used for the experiment. Results of the proposed method outperformed other methods in terms of equal error rate (EER).

영역기반 이미지 검색을 위한 칼라 이미지 세그멘테이션 (Color Image Segmentation for Region-Based Image Retrieval)

  • 황환규
    • 전자공학회논문지CI
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    • 제45권1호
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    • pp.11-24
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    • 2008
  • 효율적인 저차원의 인덱싱을 제공하기 위해 이미지를 유사한 성질을 갖는 영역으로 나누고, 나누어진 영역에 대해 유사성을 비교하는 영역 기반 이미지 검색이 제안되었다. 그러나 영역 기반 이미지 검색은 이미지를 유사한 영역으로 나누기 위한 이미지 세그멘테이션 기술이 추가적으로 필요하다. 일반적인 칼라 자연 이미지의 경우 다양한 칼라와 질감 성분을 갖는 영역으로 나누는 것은 많은 어려움이 있다. 본 논문에서는 자동적인 칼라 이미지 세그멘테이션 알고리즘을 제안한다. 제안하는 세그멘테이션 방법은 양자화를 통해 칼라수를 줄이고 양자화 된 이미지를 Fisher의 클래스 선형 판별식을 이용하여 이미지의 전체적인 에지를 보여주는 그레이 레벨 이미지를 생성한다. 이렇게 얻은 그레이 레벨 에지 이미지를 지역적 임계치 비교를 통해 이진 에지 이미지로 변환하고 이진 에지의 끊어진 부분을 찾아내어 인접 에지에 연결하여 영역을 생성한다. 마지막으로 나누어진 영역간의 유사성을 비교하고 유사한 영역을 병합하여 최종 세그멘테이션 결과 이미지를 생성한다. 본 논문에서는 세그멘테이션 알고리즘을 이용한 영역 기반 이미지 검색 시스템을 구현하였으며, 다양한 실험에 의하면 제안한 세그멘테이션 방법이 다양한 이미지에 대하여 양질의 세그멘테이션 결과를 보이는 것으로 나타났다.

Automatic Extraction of Gound-glass Opacities on Lung CT Images by Histogram Analysis

  • Maekado, Masaki;Kim, Hyoung-Seop;Ishikawa, Seiji;Tsukuda, Masaaki
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.2352-2355
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    • 2003
  • In recent yeas, studies on computer aided diagnosis (CAD) using image analysis on CT images have been conducted with respect to various diseases. Extracting ground-glass opacities (GGO) on lung CT images is one of such subjects, though it has not found an established method yet. If the region of ground-glass opacities is large on CT images, it can be detected without much difficulty. On the other hand, if the region is small, it is still difficult to find it exactly. In the latter case, increasing overlooking possibility cannot be avoided according to smaller size of the region. To solve this difficulty, this paper proposes an automatic technique for extracting ground-glass opacities on lung CT images employing some statistical parameters of a gray level histogram and a differential histogram. The proposed technique is applied to some lung CT images in the performed experiment. The results are shown with discussion on future work.

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co-occurrence 행렬을 이용한 에지 검출 (Edge Detection Using the Co-occurrence Matrix)

  • 박덕준;남권문;박래홍
    • 전자공학회논문지B
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    • 제29B권11호
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    • pp.111-119
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    • 1992
  • In this paper, we propose an edge detection scheme for noisy images based on the co-occurrence matrix. In the proposed scheme based on the step edge model, the gray level information is simply converted into a bit-map, i.e., the uniform and boundary regions of an image are transformed into a binary pattern by using the local mean. In this binary bit-map pattern, 0 and 1 densely distributed near the boundary region while they are randomly distributed in the uniform region. To detect the boundary region, the co-occurrence matrix on the bit-map is introduced. The effectiveness of the proposed scheme is shown via a quantitative performance comparison to the conventional edge detection methods and the simulation results for noisy images are also presented.

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원형 탱크 내부의 기포운동에 대한 가시화 연구 (Visualization Study on Kinematics of Bubble Motion in a Water Filled Cylindrical Tank)

  • 김상문;정원택;김경천
    • 한국가시화정보학회지
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    • 제8권3호
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    • pp.41-48
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    • 2010
  • A visualization study to evaluate bubble motion in a tab water filled cylindrical tank with a varying flow rate of compressed air is conducted. The flow rate of compressed air varies from 1 to 5 L/min. Time resolved images are acquired by a high speed camera in 10 bit gray level at 100 fps and the measurement volume is irradiated by a 230 W halogen lamp. It is observed that there are three different regions; the bubble formation region, the rising bubble region and the free surface region. During the rise of bubble, the shape is changed as if an elastic body. Based on the binarized bubble image, the mean diameters of rising bubbles are estimated at beneath of the free surface. As the gas flow rate increases, the mean diameter is increased and the rising velocity also increases with buoyancy force.