• 제목/요약/키워드: 3-D Segmentation

검색결과 459건 처리시간 0.034초

초음파 영상에서 LoG 연산자를 이용한 진단 객체의 3차원 분할 (3D Segmentation of a Diagnostic Object in Ultrasound Images Using LoG Operator)

  • 정말남;곽종인;김상현;김남철
    • 대한의용생체공학회:의공학회지
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    • 제24권4호
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    • pp.247-257
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    • 2003
  • This paper proposes a three-dimensional (3D) segmentation algorithm for extracting a diagnostic object from ultrasound images by using a LoG operator In the proposed algorithm, 2D cutting planes are first obtained by the equiangular revolution of a cross sectional Plane on a reference axis for a 3D volume data. In each 2D ultrasound image. a region of interest (ROI) box that is included tightly in a diagnostic object of interest is set. Inside the ROI box, a LoG operator, where the value of $\sigma$ is adaptively selected by the distance between reference points and the variance of the 2D image, extracts edges in the 2D image. In Post processing. regions of the edge image are found out by region filling, small regions in the region filled image are removed. and the contour image of the object is obtained by morphological opening finally. a 3D volume of the diagnostic object is rendered from the set of contour images obtained by post-processing. Experimental results for a tumor and gall bladder volume data show that the proposed method yields on average two times reduction in error rate over Krivanek's method when the results obtained manually are used as a reference data.

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.

Curvature Estimation을 이용한 3차원 사람얼굴 세그멘테이션 (3D Human Face Segmentation using Curvature Estimation)

  • Seongdong Kim;Seonga Chin;Moonwon Choo
    • 한국멀티미디어학회논문지
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    • 제6권6호
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    • pp.985-990
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    • 2003
  • 본 논문에서는 3차원 사람얼굴의 굴곡표면에 대하여 특징 값들을 추출하여 회전벡터를 이용하여 회전한 후 그들을 분석, 표현하는 방법을 제안한다. 또한 실험을 통하여 정확하게 추출된 굴곡표면의 특징 값들은 3차원 사람얼굴을 세그멘테이션 하는데 적용되었다 사람얼굴의 표면은 메쉬(mesh)모델을 사용하여 파라메타를 계산, 추출하였으며, 추출된 특징 값들은 얼굴표면을 Gaussian과 Mean 곡면 분류표(classification)를 사용하여 임계 값을 사용하지 않고 3D 얼굴표면을 세그멘테이션 하였다.

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디지틀 홀로그램에서 샘플링 조건 완화를 위한 홀로그램 Segmentation (Hologram segmentation for relaxing sampling constraint in digital hologram)

  • 양훈기;류치연;김은수
    • 전자공학회논문지D
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    • 제35D권8호
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    • pp.76-81
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    • 1998
  • This paper presents a new method to synthesize a digital hologram that meets the resolution of a currently manufactured LCD while capable of displaying a 3-D object. That is accomplished by segmenting a hologram, resulting in relaxed sampling constraint. We show that the segmentation of a hologram enables us to utilize the planewave approximation and, unlike in a holographic stereogram, it does not require projection process, but directly takes fourier transform of horizontally sliced 2-D images that constitute a 3-D object, which makes it possible to reconstruct a higher resolution image with depth information. We also show that proposed hologram contains data significantly smaller than the conventional hologram does, which is quite useful for constructing wide-viewing hologram. Finally, simulation results obtained by both methods are compared.

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하학 제 1 소구치의 3 차원 CT 영상 분할 및 정합 연구 (A Study on 3D CT Image Segmentation and Registration of Mandibular First Premolar)

  • 진경찬;전경진
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2006년도 춘계학술대회 논문집
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    • pp.175-176
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    • 2006
  • The aim of the 3D medical imaging is to facilitate the creation of clinically usable image-based algorithm. Clinically usable imaging algorithm for image analysis requires a high degree of interaction to verify and correct results from registration algorithms, such as the Insight Toolkit (ITK) and the Visualization Toolkit (VTK) which are the class libraries. ITK provides segmentation algorithms and VTK has powerful 3D visualization. However, to apply those libraries to the medical images such as Computerized Tomography (CT), the algorithm based on the interactive construction and modification of data objects are necessary. In this paper we showed the 3D registration about mandibular premolar of human teeth acquired by micro-CT scanner. Also, we used the ITK to find the contour of pulp layer of premolar, furthermore, the 3D imaging was visualized with VTK designed to create one kind of view on the data of 3D visualization. Finally, we evaluated that the volume model of pulp layer would be useful for the tooth morphology in dental medicine.

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수리 형태학 기반의 움직임 정보를 이용한 연속영상의 계층적 3차원 분할 (Hierarchical 3D Sgmentation of Image Sequence Using Motion Information Based on Mathematical Morphology)

  • 여영준;송근원;박영식;김기석;하영호
    • 전자공학회논문지S
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    • 제34S권7호
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    • pp.78-88
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    • 1997
  • A three dimensional-two spatical dimensions plus time-image segmentation is widely used in a very low bit rate image sequence coding because it can solve the region correspondence problem. Mathematical morphology is a very efficient tool for the segmentation because it deals well with geometric features such as size, shape, contrast and connectivity. But if the motion in the image sequence is large in time axis, the conventional 3D morphological segmentation algorithm have difficulty in solving region correspondence problem. To alleviate this problem, we propose the hierarchical image sequence segmentation algorithm that uses the region motion information. Since the motion of a region in previous level affects that in current level uses the previous motion information to increase region correspondence. Simulation result shows improved performance for sequence frames with large motion.

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A Fast Ground Segmentation Method for 3D Point Cloud

  • Chu, Phuong;Cho, Seoungjae;Sim, Sungdae;Kwak, Kiho;Cho, Kyungeun
    • Journal of Information Processing Systems
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    • 제13권3호
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    • pp.491-499
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    • 2017
  • In this study, we proposed a new approach to segment ground and nonground points gained from a 3D laser range sensor. The primary aim of this research was to provide a fast and effective method for ground segmentation. In each frame, we divide the point cloud into small groups. All threshold points and start-ground points in each group are then analyzed. To determine threshold points we depend on three features: gradient, lost threshold points, and abnormalities in the distance between the sensor and a particular threshold point. After a threshold point is determined, a start-ground point is then identified by considering the height difference between two consecutive points. All points from a start-ground point to the next threshold point are ground points. Other points are nonground. This process is then repeated until all points are labelled.

다시점 객체 공분할을 이용한 2D-3D 물체 자세 추정 (2D-3D Pose Estimation using Multi-view Object Co-segmentation)

  • 김성흠;복윤수;권인소
    • 로봇학회논문지
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    • 제12권1호
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    • pp.33-41
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    • 2017
  • We present a region-based approach for accurate pose estimation of small mechanical components. Our algorithm consists of two key phases: Multi-view object co-segmentation and pose estimation. In the first phase, we explain an automatic method to extract binary masks of a target object captured from multiple viewpoints. For initialization, we assume the target object is bounded by the convex volume of interest defined by a few user inputs. The co-segmented target object shares the same geometric representation in space, and has distinctive color models from those of the backgrounds. In the second phase, we retrieve a 3D model instance with correct upright orientation, and estimate a relative pose of the object observed from images. Our energy function, combining region and boundary terms for the proposed measures, maximizes the overlapping regions and boundaries between the multi-view co-segmentations and projected masks of the reference model. Based on high-quality co-segmentations consistent across all different viewpoints, our final results are accurate model indices and pose parameters of the extracted object. We demonstrate the effectiveness of the proposed method using various examples.

Semiautomatic Three-Dimensional Threshold-Based Cardiac Computed Tomography Ventricular Volumetry in Repaired Tetralogy of Fallot: Comparison with Cardiac Magnetic Resonance Imaging

  • Hyun Woo Goo
    • Korean Journal of Radiology
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    • 제20권1호
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    • pp.102-113
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    • 2019
  • Objective: To assess the accuracy and potential bias of computed tomography (CT) ventricular volumetry using semiautomatic three-dimensional (3D) threshold-based segmentation in repaired tetralogy of Fallot, and to compare them to those of two-dimensional (2D) magnetic resonance imaging (MRI). Materials and Methods: This retrospective study evaluated 32 patients with repaired tetralogy of Fallot who had undergone both cardiac CT and MRI within 3 years. For ventricular volumetry, semiautomatic 3D threshold-based segmentation was used in CT, while a manual simplified contouring 2D method was used in MRI. The indexed ventricular volumes were compared between CT and MRI. The indexed ventricular stroke volumes were compared with the indexed arterial stroke volumes measured using phase-contrast MRI. The mean differences and degrees of agreement in the indexed ventricular and stroke volumes were evaluated using Bland-Altman analysis. Results: The indexed end-systolic (ES) volumes showed no significant difference between CT and MRI (p > 0.05), while the indexed end-diastolic (ED) volumes were significantly larger on CT than on MRI (93.6 ± 17.5 mL/m2 vs. 87.3 ± 15.5 mL/m2 for the left ventricle [p < 0.001] and 177.2 ± 39.5 mL/m2 vs. 161.7 ± 33.1 mL/m2 for the right ventricle [p < 0.001], respectively). The mean differences between CT and MRI were smaller for the indexed ES volumes (2.0-2.5 mL/m2) than for the indexed ED volumes (6.3-15.5 mL/m2). CT overestimated the stroke volumes by 14-16%. With phase-contrast MRI as a reference, CT (7.2-14.3 mL/m2) showed greater mean differences in the indexed stroke volumes than did MRI (0.8-3.3 mL/m2; p < 0.005). Conclusion: Compared to 2D MRI, CT ventricular volumetry using semiautomatic 3D threshold-based segmentation provides comparable ES volumes, but overestimates the ED and stroke volumes in patients with repaired tetralogy of Fallot.

Gradient Field 기반 3D 포인트 클라우드 지면분할 기법 (Gradient field based method for segmenting 3D point cloud)

  • 호앙;푸옹;조성재;장위강;문명운;심성대;곽기호;조경은
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2016년도 추계학술발표대회
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    • pp.733-734
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    • 2016
  • This study proposes a novel approach for ground segmentation of 3D point cloud. We combine two techniques: gradient threshold segmentation, and mean height evaluation. Acquired 3D point cloud is represented as a graph data structures by exploiting the structure of 2D reference image. The ground parts nearing the position of the sensor are segmented based on gradient threshold technique. For sparse regions, we separate the ground and nonground by using a technique called mean height evaluation. The main contribution of this study is a new ground segmentation algorithm which works well with 3D point clouds from various environments. The processing time is acceptable and it allows the algorithm running in real time.