Detection of the lumen boundary in the coronary artery disease

Abstract

The intravascular ultrasound (IVUS) modality is used by the medical practitioner to detect the coronary artery disease called atherosclerosis, which is the hardening of the artery wall and subsequently narrow the blood vessel. In this paper, we present the segmentation method for detecting the lumen border of a coronary artery using IVUS images. The automated segmentation used is Otsu threshold, binary-morphological operation and empirical threshold. Thirty samples of IVUS images inclusive of the ground truth (manual tracings) were obtained from Computer Vision Centre, Bellaterra, Dept. Matematica Aplicada i Anàlisi, Universitat de Barcelona, Barcelona was used in this study. The result of the proposed automated segmentation is then compared with the ground truth provided. The segmentation performance of the proposed method is measured using Jaccard Index (JI), Dice Similarity Index (DI), Hausdorff Distance (HD), Area Overlapped Error (AOE) and Percentage Area Difference (PAD). The Bland Altman Plot is used to show the variation between the proposed automatic segmentation and ground truth. The results obtained show that the segmentation performance based on JI, DI, AOE and PAD of the proposed method is reasonably good when compared to other existing segmentation methods. However, further improvement is needed to obtain better HD value.