Velocity guided segmentation of phase contrast magnetic resonance angiography

Abstract

Atherosclerosis, the precursor to acute events such as myocardial infarction and stroke, is a focal inflammatory disease that is influenced by local hemodynamic forces such as wall shear stress (WSS). Phase contrast (PC) MRI is an established method that encodes blood velocity into the phase of an image. A requisite step for the calculation of WSS from PC-MRI data is delineation of the vasculature. Previous automatic segmentation algorithms have primarily relied on the image magnitude. Phase based segmentation algorithms have reduced the phase data to image features prior to segmentation. We outline a novel method that directly incorporates phase data as an additional external force in an active model. We demonstrate improved segmentation results over current methods on both synthetic and real data.

Coupling anatomical and functional information for the computer-aided delineation of Phase-Contrast MRI images using active contours

“…Section II presents the proposed method, as a refinement of the previously proposed work of R. L. Janiczek et al [1]. Before concluding, preliminary results are presented in section III, focusing on the potential of the proposed coupling for active-contour-based vessel delineation.…”

“…Indeed, gradients (generally sources of external forces) computed in noisy areas are so high that those related to vessels boundaries appear almost negligible to be usable for segmentation purposes. To overcome this difficulty, R. L. Janiczek et al [1] proposed to use a phase quality map, acting as a statistical spatial filtering of noisy gradient fields, while preserving those related to the vessel area. Nevertheless, according to the formulation proposed in [1], the phase quality map is not attached to the specificity of data encountered in phase image, in order to ensure the removal of noisy gradient fields (i.e.…”

“…To overcome this difficulty, R. L. Janiczek et al [1] proposed to use a phase quality map, acting as a statistical spatial filtering of noisy gradient fields, while preserving those related to the vessel area. Nevertheless, according to the formulation proposed in [1], the phase quality map is not attached to the specificity of data encountered in phase image, in order to ensure the removal of noisy gradient fields (i.e. functional information related to noisy areas) while preserving useful gradient fields (i.e.…”

“…Another recent interesting proposal dealt with the integration of the functional information (phase image) as an additional external force allowing to guide contour towards vasculature boundaries [1]. In this paper, the authors proposed to couple this external force to the one provided by the magnitude image.…”

“…As recently underlined [1], the primary used information for automatic delineation purposes is the magnitude image. For instance, this has been recently considered by Herment et al [2] using popular active contours exclusively guided by the anatomical information embedded in the magnitude image.…”