  In this paper, a novel method for lumen boundary identification is proposed
using Neutrosophic c_means. This method clusters pixels of the intravascular
optical coherence tomography image into several clusters using indeterminacy
and Neutrosophic theory, which aims to detect the boundaries. Intravascular
optical coherence tomography images are cross-sectional and high-resolution
images which are taken from the coronary arterial wall. Coronary Artery Disease
cause a lot of death each year. The first step for diagnosing this kind of
diseases is to detect lumen boundary. Employing this approach, we obtained
0.972, 0.019, 0.076 mm2, 0.32 mm, and 0.985 as mean value for Jaccard measure
(JACC), the percentage of area difference (PAD), average distance (AD),
Hausdorff distance (HD), and dice index (DI), respectively. Based on our
results, this method enjoys high accuracy performance.
