• 제목/요약/키워드: Brain Segmentation

검색결과 125건 처리시간 0.024초

기울기 벡터 플로우를 이용한 뇌출혈의 3차원 모델링 (3D Modeling of Cerebral Hemorrhage using Gradient Vector Flow)

  • 최석윤
    • 한국방사선학회논문지
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    • 제18권3호
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    • pp.231-237
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    • 2024
  • 뇌손상에서 생존자의 경우 지속적인 장애를 유발하고 뇌출혈에 따른 경막외 혈종(EDH) 및 경막하 혈종(SDH)은 주요 임상 질환 중 하나라고 볼 수 있다. 본 연구에서는 컴퓨터단층검사(CT; Computed Tomography) 영상을 기반으로 뇌출혈에 따른 혈종을 자동 분할하고 3차원으로 모델링하고자 하였다. 혈종의 자동 분할을 위해서 개선된 GVF(gradient vector flow) 알고리즘을 구현하였다. 영상으로부터 경사 벡터를 계산과 반복계산을 거친 후 자동 분할을 하고 분할 좌표를 이용해서 3차원 모델을 생성하였다. 실험결과, 혈종의 경계에 대해서 정확하게 분할 성공하였다. 경계 부분과 얇은 혈종부분에서도 결과가 좋은 것으로 나타났고, 3차원 모델을 통해서 여러 방향에서 혈종의 강도, 확산 방향, 면적 등을 알 수 있었다. 본 연구에서 개발 한 뇌출혈 부위의 평면정보와 3차원 모델은 의료진에게 보조적인 진단자료로서 활용 될 수 있을 것으로 판단한다.

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.

Contrast Enhancement for Segmentation of Hippocampus on Brain MR Images

  • Sengee, Nyamlkhagva;Sengee, Altansukh;Adiya, Enkhbolor;Choi, Heung-Kook
    • 한국멀티미디어학회논문지
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    • 제15권12호
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    • pp.1409-1416
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    • 2012
  • An image segmentation result depends on pre-processing steps such as contrast enhancement, edge detection, and smooth filtering etc. Especially medical images are low contrast and contain some noises. Therefore, the contrast enhancement and noise removal techniques are required in the pre-processing. In this study, we present an extension by a novel histogram equalization in which both local and global contrast is enhanced using neighborhood metrics. When checking neighborhood information, filters can simultaneously improve image quality. Most important is that original image information can be used for both global brightness preserving and local contrast enhancement, and image quality improvement filtering. Our experiments confirmed that the proposed method is more effective than other similar techniques reported previously.

Three Dimensional Segmentation in PCNN

  • Nishi, Naoya;Tanaka, Masaru;Kurita, Takio
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -2
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    • pp.802-805
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    • 2002
  • In the three-dimensional domain image expressed with two-dimensional slice images, such as fMRI images and multi-slice CT images, we propose the three-dimensional domain automatic segmentation for the purpose of extracting region. In this paper, we segmented each domain from the fMRI images of the head of people and monkey. We used the neural network "Pulse-Coupled Neural Network" which is one of the models of visual cortex of the brain based on the knowledge from neurophysiology as the technique. By using this technique, we can segment the region without any learning. Then, we reported the result of division of each domain and extraction to the fMRI slice images of human's head using "three-dimensional Pulse-Coupled Neural Network" which is arranged and created the neuron in the shape of a three-dimensional lattice.

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레벨 셋 방법을 이용한 뇌 MR 영상에서 해마영역 분할 (A Hippocampus Segmentation in Brain MR Images using Level-Set Method)

  • 이영승;최흥국
    • 한국멀티미디어학회논문지
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    • 제15권9호
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    • pp.1075-1085
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    • 2012
  • 영상분할은 의료 임상연구에서 가장 중요한 과정 중의 하나이다. 특히 뇌 MRI영상에서 해마의 위축은 알츠하이머병 진행과정의 초기 특정 표지자로서 해마의 볼륨은 초기 알츠하이머병의 임상적 진단에 도움이 된다. 정확한 볼륨 측정에 있어서 해마 영역의 분할은 중요한 역할을 한다. 하지만 MRI 영상에서 해마영역은 낮은 대조도, 낮은 신호 대 잡음 비율, 불연속성 경계의 특징을 보이며, 이러한 특징들은 MRI 영상에서 해마의 정확한 분할을 어렵게 만든다. 이 문제를 해결하기 위해 전처리 과정으로 실험영상에서 관심영역을 선택한 후 반전영상과 원본영상과의 차영상 대조도를 향상시킨 후 비등방성 확산(Anisotropic diffusion) 필터링, 가우시안(Gaussian) 필터링을 수행하였다. 마지막으로 두 개의 레벨 셋(Level Set)기반의 동적 윤곽선(Active Contour) 모델을 결합하여 해마를 분할하는 방법을 제안하였다. 제안된 해마분할방법의 유효성을 다양한 방법으로 평가한 결과 제안된 해마분할방법은 분할 속도와 정확도 면에서 뚜렷하게 개선이 되었음을 확인하였다. 결론적으로 제안된 방법이 해마와 같은 특징을 가진 영역을 분할하는데 적합하다고 할 수 있다. 향후 다른 연구 기법들과 결합할 경우 더욱 잠재성이 증대될 수 있을 것이다.

Measurement of Apparent Diffusion Coefficient Values from Diffusion-Weighted MRI: A Comparison of Manual and Semiautomatic Segmentation Methods

  • Kim, Seong Ho;Choi, Seung Hong;Yoon, Tae Jin;Kim, Tae Min;Lee, Se-Hoon;Park, Chul-Kee;Kim, Ji-Hoon;Sohn, Chul-Ho;Park, Sung-Hye;Kim, Il Han
    • Investigative Magnetic Resonance Imaging
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    • 제19권2호
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    • pp.88-98
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    • 2015
  • Purpose: To compare the interobserver and intraobserver reliability of mean apparent diffusion coefficient (ADC) values using contrast-enhanced (CE) T1 weighted image (WI) and T2WI as structural images between manual and semiautomatic segmentation methods. Materials and Methods: Between January 2011 and May 2013, 28 patients who underwent brain MR with diffusion weighted image (DWI) and were pathologically confirmed as having glioblastoma participated in our study. The ADC values were measured twice in manual and semiautomatic segmentation methods using CE-T1WI and T2WI as structural images to obtain interobserver and intraobserver reliability. Moreover, intraobserver reliabilities of the different segmentation methods were assessed after subgrouping of the patients based on the MR findings. Results: Interobserver and intraobserver reliabilities were high in both manual and semiautomatic segmentation methods on CE-T1WI-based evaluation, while interobserver reliability on T2WI-based evaluation was not high enough to be used in a clinical context. The intraobserver reliability was particularly lower with the T2WI-based semiautomatic segmentation method in the subgroups with involved $lobes{\leq}2$, with partially demarcated tumor borders, poorly demarcated inner margins of the necrotic portion, and with perilesional edema. Conclusion: Both the manual and semiautomatic segmentation methods on CE-T1WI-based evaluation were clinically acceptable in the measurement of mean ADC values with high interobserver and intraobserver reliabilities.

Morphology Operations on CUDA To Remove Skull on MRI Images

  • 요니 셉티안;최흥국
    • 한국멀티미디어학회:학술대회논문집
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    • 한국멀티미디어학회 2012년도 춘계학술발표대회논문집
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    • pp.205-208
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    • 2012
  • Nowadays GPU (Graphic Process Unit) is not only used to show and render some images, but also for another computation. In this paper, we tried to use GPU to do some morphology operations to remove skull from axial MRI images. This skull removing process is an important step in brain segmentation because we would like to work with the brain only, without any skull on it. The result shows that simple morphology operations to remove skull has been successfully applied on MRI images, but there are still many parts that can be develop to get better images.

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The Alpha Subunit of Go Interacts with Promyelocytic Leukemia Zinc Finger Protein

  • Ghil Sung-Ho
    • 대한의생명과학회지
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    • 제10권4호
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    • pp.407-413
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    • 2004
  • Heterotrimeric GTP binding proteins (G proteins) transduce signals of a variety of hormones and neurotransmitters. Go is one of the most abundant G proteins in the brain and classified as the Gi/Go family due to their sequence homology to Gi proteins. While the Gi proteins inhibit adenylyl cyclase and decrease the intracellular cAMP concentration, the functions of Go is not clearly understood despite their sequence homology to Gi. The promeylocytic leukemia zinc finger protein (PLZF) is a DNA binding transcription factor and is expressed highly in central nervous system (CNS). Several studies reported that PLZF may be involved in regulation segmentation/differentiation during CNS development. Here, I report that the alpha subunit of Go (Go ) interacts with PLZF. The interaction between Goa and PLZF was verified by using GST pulldown assay and co-immunoprecipitation. Our findings indicate that Goa could modulate gene expression via interaction with PLZF during neuronal or brain development.

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Multi-threshold와 Vectorgram을 이 강한 Brain 영상 분할 (Segmentation of Brain Image Using Multi-threshold and Vectorgram)

  • 이병일;최흥국
    • 한국멀티미디어학회:학술대회논문집
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    • 한국멀티미디어학회 2000년도 추계학술발표논문집
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    • pp.262-265
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    • 2000
  • 영상에서의 경계선추출은 영상의 강도의 변화를 이용한 경계영역의 가시화 기법이므로 gray level 영상이 가지는 강도를 이용하여 에지를 찾을 수 있다. 뇌 영상에는 MRI 영상과 같이 해부학적인 정보가 큰 영상과, PET 영상같이 perfusion으로 분석해야 할 영상이 있는데 그 경계가 뚜렷한 MRI 영상과 달리 PET 뇌 영상은 영상의 특성상 경계영역의 구분이 모호한 실정이다. 본 논문에서는 이러한 영상의 특성에 따라 뇌 영상에서 영상 강도에 대해 등분할을 한 후 vectorgram에서 magnitude의 영역을 선택하여 영상을 분할 하였다. 그리고 PET 와 MRI영상과 현미경 영상에 대한 결과를 비교하였다. Vertcrgram은 에지정보를 가지는 영상에 대해 벡터요소를 그래프화 한 것으로 방향성에 대한 평가를 통해 영역 분할을 하였다. 이러한 PET 영상의 2차원 분할 방법은 3차원 PET 영상 분석에 응용될 수 있을 것이다.

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A Functional Mapping Workstation of Human Brain Images

  • 백철화;김태우;송명진;유현선;김원기
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1996년도 추계학술대회
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    • pp.301-303
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    • 1996
  • A platform is developed for fast and effective functional mapping of human brain, which can allow semi-automatically the whole processes of an image segmentation, a fusion of MR and PET images, and 3-D rendering of volumetric data, including DICOM-based image transfers from PACS archiver within a short period of time.

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