• Title/Summary/Keyword: 컴퓨터 단층 영상

검색결과 377건 처리시간 0.032초

Computer Aided Diagnosis Applications for the Differential Diagnosis of Infarction: Apply on Brain CT Image (뇌경색 감별진단을 위한 컴퓨터보조진단 응용: Brain CT Images 적용)

  • Park, Hyong-Hu;Cho, Mun-Joo;Im, In-Chul;Lee, Jin-Soo
    • Journal of the Korean Society of Radiology
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    • 제10권8호
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    • pp.645-652
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    • 2016
  • In this study, based on the analysis of texture feature values of statistical properties. And we examined the normal and the applicability of the computer-aided diagnosis of cerebral infarction in the brain computed tomography images. The experiment was analyzed to evaluate the ROC curve recognition rate of disease using six parameters representing the feature values of the texture. As a result, it showed average mean 88%, variance 92%, relative smoothness 94%, uniformity of 88%, a high disease recognition rate of entropy 84%. However, it showed a slightly lower disease recognition rate and 58% for skewness. In the analysis using ROC curve, the area under the curve for each parameter indicates 0.886 (p = 0.0001) or more, resulted in a meaningful recognition of the disease. Further, to determine the cut-off values for each parameter are determined to be the prediction of disease through the computer-aided diagnosis.

Development of Graphical Solution for Computer-Assisted Fault Diagnosis: Preliminary Study (컴퓨터 원용 결함진단을 위한 그래픽 솔루션 개발에 관한 연구)

  • Yoon, Han-Bean;Yun, Seung-Man;Han, Jong-Chul;Cho, Min-Kook;Lim, Chang-Hwy;Heo, Sung-Kyn;Shon, Cheol-Soon;Kim, Seong-Sik;Lee, Seok-Hee;Lee, Suk;Kim, Ho-Koung
    • Journal of the Korean Society for Nondestructive Testing
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    • 제29권1호
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    • pp.36-42
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    • 2009
  • We have developed software for converting the volumetric voxel data obtained from X-ray computed tomography(CT) into computer-aided design(CAD) data. The developed software can used for non-destructive testing and evaluation, reverse engineering, and rapid prototyping, etc. The main algorithms employed in the software are image reconstruction, volume rendering, segmentation, and mesh data generation. The feasibility of the developed software is demonstrated with the CT data of human maxilla and mandible bones.

A Case of Ependymoma in a Dog; Computed Tomography, Histopathological and Immunohistochemical Findings (개에서 발생한 뇌실막종 증례; 컴퓨터 단층영상, 조직병리학적 그리고 면역조직화학적 소견)

  • Lee, Hee-Chun;Kim, Na-Hyun;Cho, Kyu-Woan;Jung, Hae-Won;Moon, Jong-Hyun;Kim, Ji-Hyun;Sur, Jung-Hyang;Jung, Dong-In
    • Journal of Veterinary Clinics
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    • 제31권2호
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    • pp.117-120
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    • 2014
  • An 11-year-old intact female Maltese was referred because of 1 week history of cluster seizure episodes. Based on brain CT scan, brain tumor was strongly suspected. The patient was euthanized according to client's request and we performed necropsy after euthanasia. The gross findings of the postmortem coronal sections of the brain showed that the mass was relatively well-demarcated, reddish in colored, and was present inside the left lateral ventricle and compressed adjacent tissues. The tumor mass had 2 distinct histopathological features: perivascular pseudorosette-like structures and a whirl-like arrangement of fibrillary cells. The immunohistochemical profile showed strong GFAP positivity and moderate S-100 expression, sparsely dotted staining with Ki-67. Based on the histopathological and immunohistochemical findings, the present case diagnosed to ependymoma.

The Automatic Detection of Inner Boundary on EBCT Images for Airway (기도에 대한 EBCT 영상에서의 내벽 윤곽선 자동검출)

  • 김명남;조진호
    • Journal of Korea Multimedia Society
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    • 제6권6호
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    • pp.991-999
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    • 2003
  • In this paper, we proposed image acquisition techniques that can reflect anatomical airway information lot breath change by EBCT Also, we proposed new method to detect automatically boundary of inner airway for acquired slice images using this image acquisition technology. We confirmed that new method detects boundary of inner airway effectively through computer simulation that apply image data about each slice position of airway. And, we could see change for cross section area of inner airway by time change. Therefore, we think that proposed method can utilize on quantitative analysis in clinical field.

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Missing tissue compensator modeling using a digital image technique in Radiation Therapy (디지털 영상을 이용한 방사선치료용 결손조직보상체 모델링)

  • Kim, Yonng-Bum;Choi, O-Hoon
    • Proceedings of the Korea Information Processing Society Conference
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    • 한국정보처리학회 2005년도 춘계학술발표대회
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    • pp.907-910
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    • 2005
  • 방사선치료에서 결손조직의 보호를 위해 사용되는 기존의 결손조직 보상체는 체표윤곽을 얻기위해 컴퓨터단층촬영영상이나 자기공명촬영영상등의 의료영상을 이용해 왔다. 하지만 이러한 촬영을 위해서는 고가의 비용이 소요되고 방사선치료에 따른 체표윤곽의 변화에 적절히 대응하지 못하는 등의 단점이 지적되고 있다. 따라서 본 연구에서는 사용이 간편한 디지털 카메라로 환자를 촬영한 후 얻은 2차원 이미지를 이용하여 결손조직 보상체를 제작하고 이의 유용성 평가를 위해 기하학적, 선량학적 평가를 수행하였다. 그 결과, 조직결손을 보정하고 정상조직을 보호할 수 있어 임상적용의 가능성을 확인 할 수 있었다.

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Swyer Syndrome: A Case Report (Swyer 증후군: 증례 보고)

  • Hyeong Gi Choi;Sohoon Park
    • Journal of the Korean Society of Radiology
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    • 제84권5호
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    • pp.1181-1184
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    • 2023
  • Swyer syndrome is a rare form of primary amenorrhea resulting from gonadal dysgenesis. It is characterized by the presence of a female phenotype with a 46, XY karyotype. In our case, CT scans revealed the absence of the uterus and bilateral ovaries of the 16-year-old female patient. Calcific nodules were found in both inguinal areas, which were suspected to be calcified atrophic testes. A chromosomal study confirmed the diagnosis of Swyer syndrome. Herein, we report a rare case of Swyer syndrome.

Adaptation of Deep Learning Image Reconstruction for Pediatric Head CT: A Focus on the Image Quality (소아용 두부 컴퓨터단층촬영에서 딥러닝 영상 재구성 적용: 영상 품질에 대한 고찰)

  • Nim Lee;Hyun-Hae Cho;So Mi Lee;Sun Kyoung You
    • Journal of the Korean Society of Radiology
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    • 제84권1호
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    • pp.240-252
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    • 2023
  • Purpose To assess the effect of deep learning image reconstruction (DLIR) for head CT in pediatric patients. Materials and Methods We collected 126 pediatric head CT images, which were reconstructed using filtered back projection, iterative reconstruction using adaptive statistical iterative reconstruction (ASiR)-V, and all three levels of DLIR (TrueFidelity; GE Healthcare). Each image set group was divided into four subgroups according to the patients' ages. Clinical and dose-related data were reviewed. Quantitative parameters, including the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), and qualitative parameters, including noise, gray matter-white matter (GM-WM) differentiation, sharpness, artifact, acceptability, and unfamiliar texture change were evaluated and compared. Results The SNR and CNR of each level in each age group increased among strength levels of DLIR. High-level DLIR showed a significantly improved SNR and CNR (p < 0.05). Sequential reduction of noise, improvement of GM-WM differentiation, and improvement of sharpness was noted among strength levels of DLIR. Those of high-level DLIR showed a similar value as that with ASiR-V. Artifact and acceptability did not show a significant difference among the adapted levels of DLIR. Conclusion Adaptation of high-level DLIR for the pediatric head CT can significantly reduce image noise. Modification is needed while processing artifacts.

Image Registration by Optimization of Mutual Information (상호정보 최적화를 통한 영상정합)

  • Hong, Hel-Len;Kim, Myoung-Hee
    • The KIPS Transactions:PartB
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    • 제8B권2호
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    • pp.155-163
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    • 2001
  • In this paper, we propose an image registration method by optimization of mutual information to provide a significant infonnation from multimodality images. The method applies mutual infonnation to measure the statistical dependency'r information redundancy between the image intensities of corresponding pixels in both images, which is assumed to be maximal if the images are geometrically aligned. We show the registration results optimizing mutual information between brain MR image and brain CT image and the comparison results with additive gaussian noise. Since our method uses the native image rather than prior segmentation or feature extraction, no user interaction is required and the accuracy of registration is improved. In addition, it shows the robustness against the noise.

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Comparison of Paired and Unpaired Image-to-image Translation for 18F-FDG Delayed PET Generation (18F-FDG PET 지연영상 생성에 대한 딥러닝 이미지 생성 방법론 비교)

  • ALMASLAMANI MUATH;Kangsan Kim;Byung Hyun Byun;Sang-Keun Woo
    • Proceedings of the Korean Society of Computer Information Conference
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    • 한국컴퓨터정보학회 2023년도 제68차 하계학술대회논문집 31권2호
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    • pp.179-181
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    • 2023
  • 본 논문에서는 GAN 기반의 영상 생성 방법론을 이용해 delayed PET 영상을 생성하는 연구를 수행하였다. PET은 양전자를 방출하는 방사성 동위원소를 표지한 방사성의약품의 체내 분포를 시각화함으로서 암 세포 진단에 이용되는 의료영상 기법이다. 하지만 PET의 스캔 과정에서 방사성의약품이 체내에 분포하는 데에 걸리는 시간이 오래 걸린다는 문제점이 존재한다. 따라서 본 연구에서는 방사성의약품이 충분히 분포되지 않은 상태에서 얻은 PET 영상을 통해 목표로 하는 충분히 시간이 지난 후에 얻은 PET 영상을 생성하는 모델을 GAN (generative adversarial network)에 기반한 image-to-image translation(I2I)를 통해 수행했다. 특히, 생성 전후의 영상 간의 영상 쌍을 고려한 paired I2I인 Pix2pix와 이를 고려하지 않은 unpaired I2I인 CycleGAN 두 가지의 방법론을 비교하였다. 연구 결과, Pix2pix에 기반해 생성한 delayed PET 영상이 CycleGAN을 통해 생성한 영상에 비해 영상 품질이 좋음을 확인했으며, 또한 실제 획득한 ground-truth delayed PET 영상과의 유사도 또한 더 높음을 확인할 수 있었다. 결과적으로, 딥러닝에 기반해 early PET을 통해 delayed PET을 생성할 수 있었으며, paired I2I를 적용할 경우 보다 높은 성능을 기대할 수 있었다. 이를 통해 PET 영상 획득 과정에서 방사성의약품의 체내 분포에 소요되는 시간을 딥러닝 모델을 통해 줄여 PET 이미징 과정의 시간적 비용을 절감하는 데에 크게 기여할 수 있을 것으로 기대된다.

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Effective Volume Rendering and Virtual Staining Framework for Visualizing 3D Cell Image Data (3차원 세포 영상 데이터의 효과적인 볼륨 렌더링 및 가상 염색 프레임워크)

  • Kim, Taeho;Park, Jinah
    • Journal of the Korea Computer Graphics Society
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    • 제24권1호
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    • pp.9-16
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    • 2018
  • In this paper, we introduce a visualization framework for cell image data obtained from optical diffraction tomography (ODT), including a method for representing cell morphology in 3D virtual environment and a color mapping protocol. Unlike commonly known volume data sets, such as CT images of human organ or industrial machinery, that have solid structural information, the cell image data have rather vague information with much morphological variations on the boundaries. Therefore, it is difficult to come up with consistent representation of cell structure for visualization results. To obtain desired visual representation of cellular structures, we propose an interactive visualization technique for the ODT data. In visualization of 3D shape of the cell, we adopt a volume rendering technique which is generally applied to volume data visualization and improve the quality of volume rendering result by using empty space jittering method. Furthermore, we provide a layer-based independent rendering method for multiple transfer functions to represent two or more cellular structures in unified render window. In the experiment, we examined effectiveness of proposed method by visualizing various type of the cell obtained from the microscope which can capture ODT image and fluorescence image together.