Liver perfusion using level set methods

Abstract

The family of Level Set Methods has been successfully used by scientists and practitioners for medical image processing. Image segmentation using active implicit contours is applied in 2D and 3D medical imaging, with the most popular methods being the Fast Marching Method and the Narrow band Level Set Method. In this paper we apply level set segmentation to aid in automating the clinical challenge of measuring the contrast agent concentration in liver perfusion time series. For this, we apply implicit contour methods to time series of two-dimensional MRI images to yield accurate measurements of local image properties located relative to the shape of the liver across all images in the series. Our results show that Level Set Methods can be used to provide the necessary segmentation shape data to reliably measure local image intensities positioned relative to this shape throughout a time series, where the location and shape of the object to be tracked changes.