Lumen detection in human IVUS images using region-growing

被引：8

作者：

Brathwaite, PA ^{[1
]}

Chandran, KB ^{[1
]}

McPherson, DD ^{[1
]}

Dove, EL ^{[1
]}

机构：

[1] UNIV IOWA,DEPT BIOMED ENGN,IOWA CITY,IA 52242

来源：

COMPUTERS IN CARDIOLOGY 1996 | 1996年

关键词：

D O I：

10.1109/CIC.1996.542467

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

To assess the health of arterial tissue in intravascular ultrasound (IVUS) images, detection of luminal borders is critical. We have enhanced two automated border detection schemes using region-growing based on interpixel grayscale differences, components-labeling (CL) and dilation-erosion, and watershed segmentation (WS) to correct for leaked regions due to signal drop-out and strut artifacts. The two methods were evaluated using 8 IVUS images with and without calcium lesions. Shapes were quantitatively analyzed, and the cross-sectional lumen areas calculated from the two automated methods were compared with the areas from expert traced images. Algorithm execution times were also compared. Results: CL vs. expert traced had a mean area difference of 7 pixels (p > 0.05), WS vs expert traced had a mean area difference of 394 pixels (p < 0.05), for the leaked images. Thus region-growing with CL accurately predicts luminal areas of the artery and corrects for luminal leaks better than WS.

引用

页码：37 / 40

页数：4