특이값분해 기반 동적의료영상 재구성기법의 특징 파악을 위한 시뮬레이션 연구

• 영문명: Simulation Study for Feature Identification of Dynamic Medical Image Reconstruction Technique Based on Singular Value Decomposition
• 발행기관: 대한방사선과학회(구 대한방사선기술학회)
• 저자명: 김도휘(Do-Hui Kim) 정영진(YoungJin Jung)
• 간행물 정보: 『방사선기술과학』방사선기술과학 제42권 제2호, 119~130쪽, 전체 12쪽
• 주제분류: 의약학 > 방사선과학
• 파일형태: PDF
• 발행일자: 2019.04.30

영문 초록

Positron emission tomography (PET) is widely used imaging modality for effective and accurate functional testing and medical diagnosis using radioactive isotopes. However, PET has difficulties in acquiring images with high image quality due to constraints such as the amount of radioactive isotopes injected into the patient, the detection time, the characteristics of the detector, and the patient s motion. In order to overcome this problem, we have succeeded to improve the image quality by using the dynamic image reconstruction method based on singular value decomposition. However, there is still some question about the characteristics of the proposed technique. In this study, the characteristics of reconstruction method based on singular value decomposition was estimated over computational simulation. As a result, we confirmed that the singular value decomposition based reconstruction technique distinguishes the images well when the signal - to - noise ratio of the input image is more than 20 decibels and the feature vector angle is more than 60 degrees. In addition, the proposed methode to estimate the characteristics of reconstruction technique can be applied to other spatio-temporal feature based dynamic image reconstruction techniques. The deduced conclusion of this study can be useful guideline to apply medical image into SVD based dynamic image reconstruction technique to improve the accuracy of medical diagnosis.

목차

Ⅰ. 서 론

Ⅱ. 대상 및 방법

Ⅲ. 결 과

Ⅳ. 고 찰

Ⅴ. 결 론

키워드

특이값분해 동적의료영상 영상재구성 특징분석 모의실험 Singular value decomposition Dynamic medical image Image reconstruction Feature analysis Simulation