• Title/Summary/Keyword: ghost artifact

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Noise removal or video sequences with ,3-D anisotropic diffusion equation (3차원 이방성확산 방정식을 이용한 동영상의 영상잡음제거)

  • Lee, Seok-Ho;Choe, Eun-Cheol;Gang, Mun-Gi
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.2
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    • pp.79-86
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    • 2002
  • Nowadays there is a trend to apply the diffusion equation to image Processing. The anisotropic diffusion equation is highly favoured as a noise removal algorithm because it can remove noise while enhancing edges. However if the two dimensional anisotropic diffusion equation is applied to the noise removal of video sequences, flickering artifact due to the luminance difference between frames and ghost artifact due to the interfiltering between frames occur. In this paper the two dimensional anisotropic diffusion equation is extended to the sequence axis. The Proposed three dimensional anisotropic diffusion equation removes noise more efficiently than the two dimensional equation, and furthermore removes the flickering and ghost artifact as well.

Artifacts in Digital Radiography (디지털 방사선 시스템에서 발생하는 Artifact)

  • Min, Jung-Whan;Kim, Jung-Min;Jeong, Hoi-Woun
    • Journal of radiological science and technology
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    • v.38 no.4
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    • pp.375-381
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    • 2015
  • Digital Radiography is a big part of diagnostic radiology. Because uncorrected digital radiography image supported false effect of Patient's health care. We must be manage the correct digital radiography image. Thus, the artifact images can have effect to make a wrong diagnosis. We report types of occurrence by analyzing the artifacts that occurs in digital radiography system. We had collected the artifacts occurred in digital radiography system of general hospital from 2007 to 2014. The collected data had analyzed and then had categorize as the occurred causes. The artifacts could be categorized by hardware artifacts, software artifacts, operating errors, system artifacts, and others. Hardware artifact from a Ghost artifact that is caused by lag effect occurred most frequently. The others cases are the artifacts caused by RF noise and foreign body in equipments. Software artifacts are many different types of reasons. The uncorrected processing artifacts and the image processing error artifacts occurred most frequently. Exposure data recognize (EDR) error artifacts, the processing error of commissural line, and etc., the software artifacts were caused by various reasons. Operating artifacts were caused when the user didn't have the full understanding of the digital medical image system. System artifacts had appeared the error due to DICOM header information and the compression algorithm. The obvious artifacts should be re-examined, and it could result in increasing the exposure dose of the patient. The unclear artifact leads to a wrong diagnosis and added examination. The ability to correctly determine artifact are required. We have to reduce the artifact occurrences by understanding its characteristic and providing sustainable education as well as the maintenance of the equipments.

MR Artifacts

  • 문치웅
    • Proceedings of the KSMRM Conference
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    • 2001.11a
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    • pp.73-83
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    • 2001
  • 영상의 좋고 나쁨을 나타낼 때는 대조도, 해상도, 잡음 그리고 Artifact 등을 정량적으로 측정하거나 기준이 되는 영상과 정성적으로 비교하게 된다. 이 중에서 Artifact는 영상의 해부학적 진단에 오류를 범하게 하여 엉뚱한 병리학적 해석을 내리게 하거나 해석이 불가능하게 하기도 하므로 적절한 규명을 하여 그 원인을 제거하는 등, 응당한 조치를 취해 최상의 화질을 유지하기 위한 노력을 기울여야한다. MR 영상에서 Artifact는 기하학적 늘림(stretch), 주름(wrinkle), 왜곡(distortion), 허상(ghost), 줄(line), 눈잡음(snow noise), 신호의 증감 등과 같은 다양한 현상으로 나타나며 이들은 영상을 해석할 때 오류를 범하는 원인이 된다. Artifact의 발생원인으로는 MR 장치의 기능장애, 부적절한 영상기법의 구사, 또는 MR 영상의 고유한 성질에 기인하기도 한다. MR Artifacts의 근본적인 이해를 위해서는 MRI의 물리적 원리와 장비에 관한 이해가 필요하다. 이렇게 MR Artifact는 여러 가지 인자들이 복합적인 관계를 가지고 나타나기 때문에 분류하기가 쉽지 않지만 전형적인 양상과 원인 그리고 그에 대한 여러 가지 대책을 살펴보고자 한다.

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Evaluation of Image Quality using SE-EPI and SSH-TSE Techniques in MRDWI (자기공명확산강조영상에서 SE-EPI 와 SSH-TSE 기법을 이용한 영상의 질 평가)

  • Goo, Eun-Hoe
    • Journal of the Korean Society of Radiology
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    • v.15 no.7
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    • pp.991-998
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    • 2021
  • The purpose of this study is to investigate the image quality of the SE-EPI and SSH-TSE technique for MR DWI. Datum were analyzed for 35 PACS transmission datum(Normal part: 12 males, 13 females, Cerebral Infarction: 10(5males and 5females), and average age 68±7.32), randomly selected patients who underwent MRDWI tests. The equipment used was Ingenia CX 3.0T, SSH_TSE and SE-EPI pulse sequence and 32 Ch. head coil were used for data acquisition. Image evaluation was performed on the paired t-test and Wilcoxon tests, and was considered significant when the p value was 0.05 or less. As a result of quantitative analysis of SNR for DWI images, the mean and standard deviation values of 4 parts (WM, GM, BG, Cerebellum) in ADC (s/mm2), Diffusion b=0, 1000 images were higher in SE-EPI techniques(ADC: 120.50 ± 40, b=0: 54.50 ± 35.91, b=1000: 91.61 ± 36.63) than in SSH-TSE techniques(ADC: 99.69 ± 31.10, b=0: 43.52 ± 25.00 , b=1000: 60.74 ± 24.85)(p<0.05). The CNR values for GM-WM, BG-WM sites were also higher in SE-EPI technique (ADC: 116.08 ± 43.30, b=0:27.23 ± 09.10, b=1000: 78.50 ± 16.56) than in SSH-TSE(ADC: 101.08 ± 36.81, b=0: 23.96 ± 07.79 , b=1000: 74.30 ± 14.22). As a visual evaluation of observers, ghost artifact, magnetic susceptibility artifacts and overall image quality for SE-TSE and SSH-TSE all yielded high results from SSH-TSE techniques(ADC:3.6 ± 0.1, 2.8 ± 0.2, b=0: 4.3 ± 0.3, 3.4 ± 0.1 b=1000: 4.3 ± 0.2, 3.5 ± 0.2, p=0.000). In conclusion, the SE-EPI technique obtained an superiority in SNR and CNR measurements using SSH-TSE, SE-EPI. In the qualitative analysis, the SSH-TSE pulse sequence was obtained a high result according to the pulse sequence characteristics.