Joint estimation of shape and deformation for the detection of lesions in dynamic contrast-enhanced breast MRI

Abstract

We propose a mathematical framework for simultaneously delineating the boundary of object and estimating its temporal motion in the application of lesion detection in a dynamic contrast-enhanced (DCE) breast MRI sequence where both the appearance and the shape of region of interest is assumed to change in time. A unified energy functional for a joint segmentation and registration is proposed based on the assumption that the statistical properties of dynamic intensity curves within a region of interest are homogeneous. Our algorithm is designed to provide the morphological properties of the enhanced region and its dynamic intensity profiles, called kinetic signatures, in the analysis of DCE imagery since these features are considered as significant cues in understanding images. The proposed energy comprises a combination of a segmentation energy and a registration energy. The segmentation energy is developed based on a convex formulation being insensitive to the initialization. The registration energy is designed to compensate motion artifacts that are usually involved in the temporal imaging procedure. The major objective of this work is to provide a mathematical framework for a joint segmentation and registration on a dynamic sequence of images, and we demonstrate the mutual benefit of the estimation of temporal deformations for the registration step and the localization of regions of interest for the segmentation step. The effectiveness of the developed algorithm has been demonstrated on a number of clinical DCE breast MRI data in the application of breast lesion detection and the results show its potential to improve the accuracy and the efficiency in the diagnosis of breast cancer.