title: Fully automated segmentation and tracking of the intima media thickness in ultrasound video sequences of the common carotid artery.
abstract: The robust identification and measurement of the intima media thickness (IMT) has a high clinical relevance because it represents one of the most precise predictors used in the assessment of potential future cardiovascular events. To facilitate the analysis of arterial wall thickening in serial clinical investigations, in this paper we have developed a novel fully automatic algorithm for the segmentation, measurement, and tracking of the intima media complex (IMC) in B-mode ultrasound video sequences. The proposed algorithm entails a two-stage image analysis process that initially addresses the segmentation of the IMC in the first frame of the ultrasound video sequence using a model-based approach; in the second step, a novel customized tracking procedure is applied to robustly detect the IMC in the subsequent frames. For the video tracking procedure, we introduce a spatially coherent algorithm called adaptive normalized correlation that prevents the tracking process from converging to wrong arterial interfaces. This represents the main contribution of this paper and was developed to deal with inconsistencies in the appearance of the IMC over the cardiac cycle. The quantitative evaluation has been carried out on 40 ultrasound video sequences of the common carotid artery (CCA) by comparing the results returned by the developed algorithm with respect to ground truth data that has been manually annotated by clinical experts. The measured IMT(mean) ± standard deviation recorded by the proposed algorithm is 0.60 mm ± 0.10, with a mean coefficient of variation (CV) of 2.05%, whereas the corresponding result obtained for the manually annotated ground truth data is 0.60 mm ± 0.11 with a mean CV equal to 5.60%. The numerical results reported in this paper indicate that the proposed algorithm is able to correctly segment and track the IMC in ultrasound CCA video sequences, and we were encouraged by the stability of our technique when applied to data captured under different imaging conditions. Future clinical studies will focus on the evaluation of patients that are affected by advanced cardiovascular conditions such as focal thickening and arterial plaques.
authors.affiliation: Centre for Image Processing and Analysis-CIPA, Dublin City University, Dublin, Ireland. danailea@eeng.dcu.ie
authors.forename: Dana E
authors.initials: DE
authors.lastname: Ilea
authors.forename: Caoimhe
authors.initials: C
authors.lastname: Duffy
authors.forename: Liam
authors.initials: L
authors.lastname: Kavanagh
authors.forename: Alice
authors.initials: A
authors.lastname: Stanton
authors.forename: Paul F
authors.initials: PF
authors.lastname: Whelan
mesh_terms: D000328:Adult; D000465:Algorithms; D017536:Carotid Artery, Common / Q000000981:diagnostic imaging*; D059168:Carotid Intima-Media Thickness; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D014463:Ultrasonography / Q000379:methods*; D014743:Videotape Recording / Q000379:methods*