Computerized Analysis of Magnetic Resonance Images to Study Cerebral Anatomy in Developing Neonates

The study of cerebral anatomy in developing neonates is of great importance for the understanding of brain development during the early period of life. This dissertation therefore focuses on three challenges in the modelling of cerebral anatomy in neonates during brain development. The methods that have been developed all use Magnetic Resonance Images (MRI) as source data. To facilitate study of vascular development in the neonatal period, a set of image analysis algorithms are developed to automatically extract and model cerebral vessel trees. The whole process consists of cerebral vessel tracking from automatically placed seed points, vessel tree generation, and vasculature registration and matching. These algorithms have been tested on clinical Time-of- Flight (TOF) MR angiographic datasets. To facilitate study of the neonatal cortex a complete cerebral cortex segmentation and reconstruction pipeline has been developed. Segmentation of the neonatal cortex is not effectively done by existing algorithms designed for the adult brain because the contrast between grey and white matter is reversed. This causes pixels containing tissue mixtures to be incorrectly labelled by conventional methods. The neonatal cortical segmentation method that has been developed is based on a novel expectation-maximization (EM) method with explicit correction for mislabelled partial volume voxels. Based on the resulting cortical segmentation, an implicit surface evolution technique is adopted for the reconstruction of the cortex in neonates. The performance of the method is investigated by performing a detailed landmark study. To facilitate study of cortical development, a cortical surface registration algorithm for aligning the cortical surface is developed. The method first inflates extracted cortical surfaces and then performs a non-rigid surface registration using free-form deformations (FFDs) to remove residual alignment. Validation experiments using data labelled by an expert observer demonstrate that the method can capture local changes and follow the growth of specific sulcus

Registration and Analysis of Vascular Images

We have developed a method for rigidly aligning images of tubes. This paper presents an evaluation of the consistency of that method for three-dimensional images of human vasculature. Vascular images may contain alignment ambiguities, poorly corresponding vascular networks, and non-rigid deformations, yet the Monte Carlo experiments presented in this paper show that our method provides registrations with sub-voxel consistency in less than one minute. Our registration method builds on the principals of our ridges-and-widths tube modeling work; this registration method operates by aligning models of the tubes in a source image with subsequent target images. The registration method’s consistency results from incorporate multi-scale ridge and width measures into the model-image match metric. The method’s speed comes from the use of coarse-to-fine registration strategies that are directly enabled by our tube models and the model-image match metric. In this paper we also show that the method’s insensitivity to local, non-rigid deformations enables the visualization and quantification of the effects of such deformations

Dynamic Arterial Spin Labeling Measurements of Physiological Parameters - Permeability and Oxygenation

Arterial Spin Labeling (ASL) is an MR imaging technique which can measure the brain perfusion locally without contrast agent. The inflowing blood is labeled by inverting the magnetization of the water molecules. During the blood flow through the vascular tree and the capillary bed, the signal can be acquired at different inflow times. Thereby, the signal decays with T1. An aspect which has not yet been investigated is the dynamics of further MR parameters during the inflow. In the present work, the dynamics of the parameters T2 and T2’ of the perfusion signal are investigated. The employed MRI sequences have been developed and are presented in this thesis: a 3D-GRASE readout with variable echo time for T2 quantification, and a spin/gradient double echo double spiral 3D-GRASE readout for T2’ estimation. Further, a model has been developed which describes the behavior of the perfusion signal which includes permeability, depending on the echo time. With the acquired data it has been possible to directly derive an estimate for the local water permeability of the capillary wall. The T2’ data allows an estimation of dynamical changes of oxygenation and local apparent venous volume in the direct vicinity of the inflowing blood water spins. The double echo spiral sequence in conjunction with ASL can in principle acquire perfusion and oxygenation simultaneously and is therefore predestined for functional imaging applications. Both techniques allow deep insights in basic local perfusion mechanisms

Age-Related Macular Degeneration and Diabetic Retinopathy

This reprint includes contributions from leaders in the field of personalized medicine in ophthalmology. The contributions are diverse and cover pre-clinical and clinical topics. We hope you enjoy reading the articles