An Inverse Scattering Algorithm for the Segmentation of the Luminal Border on Intravascular Ultrasound Data

Authors:
E. Gerardo Mendizabal-Ruiz;George Biros;Ioannis A. Kakadiaris
Affiliations:
Computational Biomedicine Lab, Departments of Computer Science, Electrical and Computer Engineering, and Biomedical Engineering, University of Houston, Houston;Department of Biomedical Engineering and School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta;Computational Biomedicine Lab, Departments of Computer Science, Electrical and Computer Engineering, and Biomedical Engineering, University of Houston, Houston
Venue:
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Year:
2009

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Abstract

Intravascular ultrasound (IVUS) is a catheter-based medical imaging technique that produces cross-sectional images of blood vessels and is particularly useful for studying atherosclerosis. In this paper, we present a novel method for segmentation of the luminal border on IVUS images using the radio frequency (RF) raw signal based on a scattering model and an inversion scheme. The scattering model is based on a random distribution of point scatterers in the vessel. The per-scatterer signal uses a differential backscatter cross-section coefficient (DBC) that depends on the tissue type. Segmentation requires two inversions: a calibration inversion and a reconstruction inversion. In the calibration step, we use a single manually segmented frame and then solve an inverse problem to recover the DBC for the lumen and vessel wall (*** l and *** w , respectively) and the width of the impulse signal *** . In the reconstruction step, we use the parameters from the calibration step to solve a new inverse problem: for each angle *** i of the IVUS data, we reconstruct the lumen-vessel wall interface. We evaluated our method using three 40MHz IVUS sequences by comparing with manual segmentations. Our preliminary results indicate that it is possible to segment the luminal border by solving an inverse problem using the IVUS RF raw signal with the scatterer model.