Automatic segmentation of the left ventricle cavity and myocardium in MRI data

A novel approach for the automatic segmentation has been developed to extract the epi-cardium and endo-cardium boundaries of the left ventricle (lv) of the heart. The developed segmentation scheme takes multi-slice and multi-phase magnetic resonance (MR) images of the heart, transversing the short-axis length from the base to the apex. Each image is taken at one instance in the heart's phase. The images are segmented using a diffusion-based filter followed by an unsupervised clustering technique and the resulting labels are checked to locate the (lv) cavity. From cardiac anatomy, the closest pool of blood to the lv cavity is the right ventricle cavity. The wall between these two blood-pools (interventricular septum) is measured to give an approximate thickness for the myocardium. This value is used when a radial search is performed on a gradient image to find appropriate robust segments of the epi-cardium boundary. The robust edge segments are then joined using a normal spline curve. Experimental results are presented with very encouraging qualitative and quantitative results and a comparison is made against the state-of-the art level-sets method

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

Numerical methods for dynamic Magnetic Resonance Imaging

Nel rapporto vengono presentati alcuni metodi nuemrici per la ricostruzione di immagini dinamiche di risonanza magnetica utilizzando anche informazioni a priori, attraverso una formula unificata che li descrive tutti. In particolare, si studia l'uso delle basi B-spline e della regolarizzazione nella ricostruzione di immagini dinamiche di risonanza magnetica

Dynamic Multivariate Simplex Splines For Volume Representation And Modeling

Volume representation and modeling of heterogeneous objects acquired from real world are very challenging research tasks and playing fundamental roles in many potential applications, e.g., volume reconstruction, volume simulation and volume registration. In order to accurately and efficiently represent and model the real-world objects, this dissertation proposes an integrated computational framework based on dynamic multivariate simplex splines (DMSS) that can greatly improve the accuracy and efficacy of modeling and simulation of heterogenous objects. The framework can not only reconstruct with high accuracy geometric, material, and other quantities associated with heterogeneous real-world models, but also simulate the complicated dynamics precisely by tightly coupling these physical properties into simulation. The integration of geometric modeling and material modeling is the key to the success of representation and modeling of real-world objects. The proposed framework has been successfully applied to multiple research areas, such as volume reconstruction and visualization, nonrigid volume registration, and physically based modeling and simulation

Functional Neuroanatomy of Dynamic Visuo-Spatial Imagery

The aim of this thesis was the examination of the neural bases of dynamic visuo-spatial imagery. In addition to the assessment of brain activity during dy-namic visuo-spatial imagery using single-trial functional magnetic resonance im-aging (fMRI) and slow cortical potentials (SCPs), several methodological issues have been investigated. The theoretical part of this thesis consists of a selective overview of fMRI and SCPs, and of the advantages of their combination for functional neuroimaging (chapter 2). The methodological and empirical chapters include: Ø the presentation of a new, highly accurate and practicable method for the co-registration of MRI- and EEG-data (chapter 3), Ø the description of the increase in the accuracy of SCP mapping resulting from the use of individual electrode coordinates and realistic head models (chapter 4), Ø the description of regional differences in the consistency of brain activity across several executions of the same task type, as assessed by a new analysis con-cept based on single-trial fMRI data (chapter 5), Ø the demonstration of the involvement of premotor regions in dynamic visuo-spatial imagery, as assessed via a combination of single-trial fMRI and SCPs (chapter 6), Ø the description of a combined fMRI-SCP investigation in which earlier findings concerning individual differences in neural efficiency during dynamic imagery could not be replicated (chapter 7)