Image-based ECG sampling of IVUS sequences

Abstract

Longitudinal motion artifacts in IntraVascular UltraSound (IVUS) sequences hinders a properly 3D reconstruction and vessel measurements. Most of current techniques base on the ECG signal to obtain a gated pullback without the longitudinal artifact by using a specific hardware or the ECG signal itself. The potential of IVUS images processing for phase retrieval still remains little explored. In this paper, we present a fast forward image-based algorithm to approach ECG sampling. Inspired on the fact that maximum and minimum lumen areas are related to end-systole and end-diastole, our cardiac phase retrieval is based on the analysis of tissue density of mass along the sequence. The comparison between automatic and manual phase retrieval (0.07 ± 0.07 mm. of error) encourages a deep validation contrasting with ECG signals.

Improving Cardiac Phase Extraction in IVUS Studies by Integration of Gating Methods

“…For methods in the latter category, a set of features are used to measure the variations between adjacent images: crosscorrelation [5], [9], [10], [12], sum of squared distances (SSD) [14], local mean variation [4], [11], [12], [15], Gabor filters' descriptors [8] or radial blurring [13]. It is worth noting that the blurring feature measures the motion by perturbations over the transducer probe being not sensitive to topological variations, while features like cross-correlation or SSD measure by differences between adjacent frames.…”