• Title/Summary/Keyword: Level Set Segmentation

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Automatic Tumor Segmentation Method using Symmetry Analysis and Level Set Algorithm in MR Brain Image (대칭성 분석과 레벨셋을 이용한 자기공명 뇌영상의 자동 종양 영역 분할 방법)

  • Kim, Bo-Ram;Park, Keun-Hye;Kim, Wook-Hyun
    • Journal of the Institute of Convergence Signal Processing
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    • v.12 no.4
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    • pp.267-273
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    • 2011
  • In this paper, we proposed the method to detect brain tumor region in MR images. Our method is composed of 3 parts, detection of tumor slice, detection of tumor region and tumor boundary detection. In the tumor slice detection step, a slice which contains tumor regions is distinguished using symmetric analysis in 3D brain volume. The tumor region detection step is the process to segment the tumor region in the slice distinguished as a tumor slice. And tumor region is finally detected, using spatial feature and symmetric analysis based on the cluster information. The process for detecting tumor slice and tumor region have advantages which are robust for noise and requires less computational time, using the knowledge of the brain tumor and cluster-based on symmetric analysis. And we use the level set method with fast marching algorithm to detect the tumor boundary. It is performed to find the tumor boundary for all other slices using the initial seeds derived from the previous or later slice until the tumor region is vanished. It requires less computational time because every procedure is not performed for all slices.

Neighboring Elemental Image Exemplar Based Inpainting for Computational Integral Imaging Reconstruction with Partial Occlusion

  • Ko, Bumseok;Lee, Byung-Gook;Lee, Sukho
    • Journal of the Optical Society of Korea
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    • v.19 no.4
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    • pp.390-396
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    • 2015
  • We propose a partial occlusion removal method for computational integral imaging reconstruction (CIIR) based on the usage of the exemplar based inpainting technique. The proposed method is an improved version of the original linear inpainting based CIIR (LI-CIIR), which uses the inpainting technique to fill in the data missing region. The LI-CIIR shows good results for images which contain objects with smooth surfaces. However, if the object has a textured surface, the result of the LI-CIIR deteriorates, since the linear inpainting cannot recover the textured data in the data missing region well. In this work, we utilize the exemplar based inpainting to fill in the textured data in the data missing region. We call the proposed method the neighboring elemental image exemplar based inpainting (NEI-exemplar inpainting) method, since it uses sources from neighboring elemental images to fill in the data missing region. Furthermore, we also propose an automatic occluding region extraction method based on the use of the mutual constraint using depth estimation (MC-DE) and the level set based bimodal segmentation. Experimental results show the validity of the proposed system.

Data Structure Extraction of Boundary Segments by Region Labeling (영역 라벨링에 의한 경계선 세그먼트의 데이터 구조 추출)

  • 최환언;정광웅;김두영
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.17 no.1
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    • pp.80-89
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    • 1992
  • This paper presents algorithms which are region labeling and data structure of a boundary segmentation as image intermediate description process. In the method, the algorithms are region labeling, boundary segmentation, line and curve fitting and extracting data structure of each segment. As a result, a data structure of image is described by a set of region number, segment number, line or curve, starting point and end point of each segment and coefficient of line or curve. These data structures would serve for higher level processing as object recognition. For example we will use this data structure to solve the correspondence problem of stereoscopic image information. And we verified these algorithms through the image reconstruction of data structure.

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Pixel level prediction of dynamic pressure distribution on hull surface based on convolutional neural network (합성곱 신경망 기반 선체 표면 압력 분포의 픽셀 수준 예측)

  • Kim, Dayeon;Seo, Jeongbeom;Lee, Inwon
    • Journal of the Korean Society of Visualization
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    • v.20 no.2
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    • pp.78-85
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    • 2022
  • In these days, the rapid development in prediction technology using artificial intelligent is being applied in a variety of engineering fields. Especially, dimensionality reduction technologies such as autoencoder and convolutional neural network have enabled the classification and regression of high-dimensional data. In particular, pixel level prediction technology enables semantic segmentation (fine-grained classification), or physical value prediction for each pixel such as depth or surface normal estimation. In this study, the pressure distribution of the ship's surface was estimated at the pixel level based on the artificial neural network. First, a potential flow analysis was performed on the hull form data generated by transforming the baseline hull form data to construct 429 datasets for learning. Thereafter, a neural network with a U-shape structure was configured to learn the pressure value at the node position of the pretreated hull form. As a result, for the hull form included in training set, it was confirmed that the neural network can make a good prediction for pressure distribution. But in case of container ship, which is not included and have different characteristics, the network couldn't give a reasonable result.

A Study on the Market Segmentation of Accessible Housing for the Elderly Using Conjoint Analysis (컨조인트 분석을 이용한 노약자를 위한 접근가능한 주택의 시장 세분화 연구)

  • Lee, So-Young;Kim, Ji-Woo
    • Journal of the Korean housing association
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    • v.26 no.4
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    • pp.11-21
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    • 2015
  • Due to the mass production of housing in Korea, homogeneous current housing may fail to represent residents' preferences, especially for the elderly. The purpose of this study is to identify the preferred properties of consumers for accessible housing and to examine whether cluster analysis can identify groups of residents with similar accessible housing preferences. Using a conjoint method, prospective users can jointly consider all accessible attributes, with cost attributes suggested by this study. Four categories (accessibility, safety, convenience, cost), 7 attributes (clear width, level difference, installation of grab bars, installation of elevators: only for single house type, non slippery floor materials, safety alarms, service control devices, cost) and 2 levels for each attribute were chosen. A total of 374 questionnaires were collected through a questionnaire survey method. This study employed ratings-based Conjoint analysis and the respondents ranked each card, which consisted of a set of accessible housing attributes. The data were analyzed using SPSS 16.0. The findings of this study have identified 3-4 clusters for each housing sub market. Each cluster has a different combination of socio-demographic characteristics and residential characteristics, and showed the relative importance or preference values for each accessible attribute of the segmentation. For the single housing, one group of people strongly preferred installation of elevator. The results suggested that better customization of housing could be more appealing to the different clusters of residents, providing accessible housing with cost limitations.

3D Reconstruction Using Segmentation of Myocardial SPECT Images (SPECT 심근영상의 영상분할을 이용한 3차원 재구성)

  • Jung, Jae-En;Lee, Sang-Bock
    • Journal of the Korean Society of Radiology
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    • v.3 no.2
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    • pp.5-10
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    • 2009
  • Myocardial imaging in SPECT (Single Photon Emission Computed tomography) scan of the gamma-ray emitting radiopharmaceuticals to patients after intravenous radiopharmaceuticals evenly spread in the heart region of interest by recording changes in the disease caused by a computer using the PSA test is to diagnose. Containing information on the functional myocardial perfusion imaging is a useful way to examine non-invasive heart disease, but the argument by noise and low resolution of the physical landscape that is difficult to give. For this paper, the level of myocardial imaging by using the three algorithms to split the video into 3-D implementation of the partitioned area to help you read the proposed plan. To solve the difficulty of reading level, interest in using the sheet set, partitioned area of the left ventricle was ranked the partitioned area was modeled as a 3-D images.

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3D Reconstruction Using Segmentation of Myocardial SPECT (SPECT 심근영상의 영상분할을 이용한 3차원 재구성)

  • Jung, Jae-Eun;Lee, Jun-Haeng;Choi, Seok-Yoon;Lee, Sang-Bock
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.6
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    • pp.2240-2245
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    • 2010
  • Myocardial imaging in SPECT (Single Photon Emission Computed tomography) scan of the gamma-ray emitting radiopharmaceuticals to patients after intravenous radiopharmaceuticals evenly spread in the heart region of interest by recording changes in the disease caused by a computer using the PSA test is to diagnose. Containing information on the functional myocardial perfusion imaging is a useful way to examine non-invasive heart disease, but the argument by noise and low resolution of the physical landscape that is difficult to give. For this paper, the level of myocardial imaging by using the three algorithms to split the video into 3-D implementation of the partitioned area to help you read the proposed plan. To solve the difficulty of reading level, interest in using the sheet set, partitioned area of the left ventricle was ranked the partitioned area was modeled as a 3-D images.

Content-Based Image Retrieval System using Feature Extraction of Image Objects (영상 객체의 특징 추출을 이용한 내용 기반 영상 검색 시스템)

  • Jung Seh-Hwan;Seo Kwang-Kyu
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.27 no.3
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    • pp.59-65
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    • 2004
  • This paper explores an image segmentation and representation method using Vector Quantization(VQ) on color and texture for content-based image retrieval system. The basic idea is a transformation from the raw pixel data to a small set of image regions which are coherent in color and texture space. These schemes are used for object-based image retrieval. Features for image retrieval are three color features from HSV color model and five texture features from Gray-level co-occurrence matrices. Once the feature extraction scheme is performed in the image, 8-dimensional feature vectors represent each pixel in the image. VQ algorithm is used to cluster each pixel data into groups. A representative feature table based on the dominant groups is obtained and used to retrieve similar images according to object within the image. The proposed method can retrieve similar images even in the case that the objects are translated, scaled, and rotated.

Hardware-based Level Set Method for Fast Lung Segmentation and Visualization (빠른 폐 분할과 가시화를 위한 그래픽 하드웨어 기반 레벨-셋 방법)

  • Park Seong-Jin;Hong He-Len;Shin Yeong-Gil
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.06b
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    • pp.268-270
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    • 2006
  • 본 논문에서는 3차원 볼륨영상에서 객체를 빠르게 분할하고 동시에 대화식으로 분할과정을 가시화하기 위하여 그래픽 하드웨어를 사용한 레벨-셋 방법을 제안한다. 이를 위하여 첫째, GPU 내에서 효율적 연산을 수행하기 위해 메모리 관리방법을 제안한다. 이는 GPU 내 텍스쳐 메모리 형식에 적합하게 데이터를 패킹하고, CPU의 주메모리와 GPU의 텍스쳐 메모리를 관리하는 방법을 제시한다. 둘째, GPU 내에서 레벨-셋 값을 갱신하는 과정을 9가지 경우로 나누어 연산을 수행하게 함으로써 연산의 효율성을 높힌다. 셋째, front의 변화를 대화식으로 확인하고, 파라미터 변경에 따른 분할 과정을 효과적으로 측정하기 위하여 그래픽 하드웨어 기반 빠른 가시화 방법을 제안한다. 본 논문에서는 제안방법을 평가하기 위하여 3차원 폐 CT 영상데이터를 사용하여 육안평가를 수행하고, 기존 소프트웨어 기반 레벨-셋 방법과 수행시간 측면에서 비교 분석한다. 본 제안방법은 소프트웨어 기반 레벨-셋 방법보다 빠르게 영상을 분할하고 동시에 가시화함으로써 데이터 량이 많은 의료응용에 효율적으로 적용이 가능하다.

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Comparative Analysis of Segmentation Methods in Psoriasis Area (건선 영역 분할기법 비교분석)

  • Yoo, Hyun-Jong;Lee, Ji-Won;Moon, Cho-I;Kim, Eun-Bin;Baek, Yoo-Sang;Jang, Sang-Hoon;Lee, OnSeok
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.10a
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    • pp.657-659
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    • 2019
  • 본 논문에서는 피부 이미지에서 건선 병변만을 가장 효과적으로 분할 할 수 있는 분할기법 선별을 목표로 한다. Interactive graph cuts (IGC)와 Level set method (LSM)를 사용하여 건선 영역을 분할한 후 Jaccard Index (JI)와 Dice Similarity Coefficient (DSC)을 사용하여 건선 영역에 효과적인 분할 방법을 제안한다.