Automatic quantitative analysis of in-stent restenosis using FD-OCT in vivo intra-arterial imaging.

Purpose: A new segmentation technique is implemented for automatic lumen area extraction and stent strut detection in intravascular optical coherence tomography (OCT) images for the purpose of quantitative analysis of in-stent restenosis (ISR). In addition, a user-friendly graphical user interface (GUI) is developed based on the employed algorithm toward clinical use.

Methods: Four clinical datasets of frequency-domain OCT scans of the human femoral artery were analyzed.

SU-E-I-90: Fast and Robust Algorithm Towards Vessel Lumen and Stent Strut Detection in Optical Coherence Tomography.

Purpose: Optical Coherence Tomography (OCT) is a catheter-based imaging method that employs near-infrared light to produce high-resolution cross-sectional intravascular images. We propose a new segmentation technique for automatic lumen area extraction and stent strut detection in intravascular OCT images for the purpose of quantitative analysis of neointimal hyperplasia (NIH).

Methods: Two clinical dataset of frequency-domainOCT scans of the human femoral artery were analyzed.