The robust measurement of the intima media thickness (IMT) of longitudinal common carotid artery (CCA) has an important clinical value because clinicians often use it as an important predictor to assess the possibility of potential cardiovascular events. The purpose of this study was to develop a fully automated algorithm to measure the IMT in the longitudinal ultrasound B-mode images. A completely automated algorithm for identification and calculation of IMT is proposed in this paper. Based on signal analysis, the algorithm can be divided into four steps. The first step is to automatically identify the lumen-intima (LI) interface points of posterior wall. Starting from the detected LI interface points, the second step uses the gradient-based method to locate the candidate media-adventitia (MA) interface points. The third step applies the canny edge detector to remove the outliers from the candidate points. The last step is to calculate the IMT from the final available points. On 35 ultrasound video sequences of the common carotid artery (CCA) taken from 13 healthy subjects, the results generated by the proposed method were compared to the manual annotated data. The proposed method yielded an IMT of 0.61 mm ± 0.085 (mean ± standard deviation) whereas the corresponding result yielded by the manual annotated ground truth data is 0.60 mm ± 0.1. The proposed method eliminates the need of manual initialization, and measures the IMT of the longitudinal CCA with high precision similar to the ones observed in the manual segmentations. It has the potential to be a suitable replacement for manual segmentation and measurement of the IMT.
목차
Abstract 1. Introduction 2. Material and Methods 2.1. Step-1 Lumen-Intima (LI) Interface Recognition 2.2. Step-2 Media-Adventitia (MA) Interface Recognition 2.3. Step-3 Outliers Removal 2.4. Step-4 Calculation of the IMT 3. Results 4. Discussion 5. Conclusions Acknowledgement References
키워드
intima media thicknessimage segmentationcommon carotid arteryultrasound
저자
Yong Chen [ College of Computer Science, Sichuan University; ChengDu city, P.R. China ]
Bo Peng [ College of Computer Science, Sichuan University; ChengDu city, P.R. China ]
DongC Liu [ College of Computer Science, Sichuan University; ChengDu city, P.R. China ]
보안공학연구지원센터(IJSIP) [Science & Engineering Research Support Center, Republic of Korea(IJSIP)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Signal Processing, Image Processing and Pattern Recognition
간기
격월간
pISSN
2005-4254
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.7 No.3