840 research outputs found

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

    Get PDF
    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

    Geometric Modeling of Thoracic Aortic Surface Morphology - Implications for Pathophysiology and Clinical Interventions

    Get PDF
    Vascular disease risk factors such as hypertension, hyperlipidemia and old age are all\ua0results of modern-day lifestyle, and these diseases are getting more and more common. One\ua0treatment option for vascular diseases such as aneurysms and dissections is endovascular\ua0aortic repair introduced in the early 1990s. This treatment uses tubular fabric covered\ua0metallic structures (endografts) that are implanted using a minimally invasive approach\ua0and placed to serve as an articial vessel in a damaged portion of the vasculature. To ensure\ua0that the interventions are successful, the endograft must be placed in the correct location,\ua0and designed to sustain the hostile biological, chemical, and mechanical conditions in the\ua0body for many years. This is an interaction that goes both ways, and keeping in mind\ua0that the endograft is a foreign object placed in the sensitive vascular system, it is also\ua0important that it does not disrupt the native conditions more than necessary.This thesis presents a segmentation and quantication methodology to accurately\ua0describe the complex morphology and motion of diseased blood vessels in vivo through a\ua0natural and intuitive description of their luminal surfaces. After methodology validation,\ua0a series of important clinical applications are performed, all based on non-invasive imaging.\ua0Firstly, it is shown that explicit surface curvature quantication is necessary when\ua0compared to relying solely on centerline curvature and estimation methods. Secondly, it is\ua0shown that endograft malapposition severity can be predicted from preoperative geometric\ua0analysis of thoracic aortic surfaces. Thirdly, a multiaxial dynamics analysis of cardiac\ua0induced thoracic aortic surface motion shows how thoracic endovascular aortic repair\ua0affects the deformations of the dierent portions of the thoracic aorta. Fourthly, the helical\ua0propagation pattern of type B aortic dissection is determined, and two distinct modes of\ua0chirality are revealed, i.e., achiral and right-handed chiral groups. Finally, the effects of\ua0thoracic endovascular aortic repair on helical and cross-sectional morphology of type B\ua0dissections are investigated revealing how acuity and chirality affects the alteration due to\ua0intraluminal lining with endografts. Thus, the work presented in this thesis contributes\ua0by adding knowledge about pathology and pathophysiology through better geometric\ua0description of surface conditions of diseased thoracic aortas. This gives clinicians insights\ua0to use in their treatment planning and provides more nuanced boundary conditions for\ua0endograft manufacturers. Comprehensive knowledge about diseases, better treatment\ua0planning, and better devices are all crucial in order to improve the outcomes of performed\ua0interventions and ultimately the quality of life for the treated patients

    Modeling of Intraluminal Surfaces of Thoracic Aortas

    Get PDF
    Vascular diseases are getting more and more common as a result of modern-day lifestyle and the fact that the population is getting older. One of the newest treatments for vascular diseases such as aneurysms and dissections is endovascular repair with endografting. This treatment uses a fabric covered metallic structure that is implanted using a minimally invasive approach to serve as an artificial vessel in a damaged region. To ensure that the interventions are successful, the endograft must be placed in the correct location, and be designed to sustain the hostile biological, chemical, and mechanical conditions in the body for many years.To accurately describe the complex mechanical conditions of the intraluminal surfaces of diseased blood vessels inside the body, this thesis presented a segmentation and quantification methodology for a natural and intuitive vessel surface description. The thesis also included some important clinical applications, all based on non-invasive temporal imaging. The results emphasized the need for explicit surface curvature quantification, as compared to relying solely on centerline curvature and estimation methods. Methods for preoperative prediction of endograft malapposition severity based on geometric analysis of thoracic aortic surfaces were introduced. Finally, a multiaxial dynamic analysis of cardiac induced thoracic aortic surface deformation showed how a thoracic endovascular aortic repair is a↵ecting the deformations of the thoracic aorta.Thus, the work presented in this thesis contributes by giving surgeons a tool to use in their treatment planning to minimize complications. Moreover, this method provides more nuanced boundary conditions so that endograft manufacturers can improve their designs to improve the quality of life for the treated patients

    Deep convolutional neural networks for segmenting 3D in vivo multiphoton images of vasculature in Alzheimer disease mouse models

    Full text link
    The health and function of tissue rely on its vasculature network to provide reliable blood perfusion. Volumetric imaging approaches, such as multiphoton microscopy, are able to generate detailed 3D images of blood vessels that could contribute to our understanding of the role of vascular structure in normal physiology and in disease mechanisms. The segmentation of vessels, a core image analysis problem, is a bottleneck that has prevented the systematic comparison of 3D vascular architecture across experimental populations. We explored the use of convolutional neural networks to segment 3D vessels within volumetric in vivo images acquired by multiphoton microscopy. We evaluated different network architectures and machine learning techniques in the context of this segmentation problem. We show that our optimized convolutional neural network architecture, which we call DeepVess, yielded a segmentation accuracy that was better than both the current state-of-the-art and a trained human annotator, while also being orders of magnitude faster. To explore the effects of aging and Alzheimer's disease on capillaries, we applied DeepVess to 3D images of cortical blood vessels in young and old mouse models of Alzheimer's disease and wild type littermates. We found little difference in the distribution of capillary diameter or tortuosity between these groups, but did note a decrease in the number of longer capillary segments (>75μm>75\mu m) in aged animals as compared to young, in both wild type and Alzheimer's disease mouse models.Comment: 34 pages, 9 figure

    Multiaxial pulsatile dynamics of the thoracic aorta and impact of thoracic endovascular repair

    Get PDF
    Purpose: The thoracic aorta is a highly mobile organ whose dynamics are altered by thoracic endovascular aorta repair (TEVAR). The aim of this study was to quantify cardiac pulsatility-induced multi-axial deformation of the thoracic aorta before and after descending aortic TEVAR. Methods: Eleven TEVAR patients (8 males and 3 females, age 57–89) underwent retrospective cardiac-gated CT angiography before and after TEVAR. 3D geometric models of the thoracic aorta were constructed, and lumen centerlines, inner and outer surface curves, and cross-sections were extracted to measure aortic arclength, centerline, inner surface, and outer surface longitudinal curvatures, as well as cross-sectional effective diameter and eccentricity for the ascending and stented aortic portions. Results: From pre- to post-TEVAR, arclength deformation was increased at the ascending aorta from 5.9 \ub1 3.1 % to 8.8 \ub1 4.4 % (P < 0.05), and decreased at the stented aorta from 7.5 \ub1 5.1 % to 2.7 \ub1 2.5 % (P < 0.05). Longitudinal curvature and diametric deformations were reduced at the stented aorta. Centerline curvature, inner surface curvature, and cross-sectional eccentricity deformations were increased at the distal ascending aorta. Conclusions: Deformations were reduced in the stented thoracic aorta after TEVAR, but increased in the ascending aorta near the aortic arch, possibly as a compensatory mechanism to maintain overall thoracic compliance in the presence of reduced deformation in the stiffened stented aorta

    Imaging Biomarkers for Carotid Artery Atherosclerosis

    Get PDF

    Imaging Biomarkers for Carotid Artery Atherosclerosis

    Get PDF

    Motion Calculations on Stent Grafts in AAA

    Get PDF
    Endovascular aortic repair (EVAR) is a technique which uses stent grafts to treat aortic aneurysms in patients at risk of aneurysm rupture. Although this technique has been shown to be very successful on the short term, the long term results are less optimistic due to failure of the stent graft. The pulsating blood flow applies stresses and forces to the stent graft, which can cause problems such as breakage, leakage, and migration. Therefore it is of importance to gain more insight into the in vivo motion behavior of these devices. If we know more about the motion patterns in well-behaved stent graft as well as ill-behaving devices, we shall be better able to distinguish between these type of behaviors These insights will enable us to detect stent-related problems and might even be used to predict problems beforehand. Further, these insights will help in designing the next generation stent grafts. Firstly, this work discusses the applicability of ECG-gated CT for measuring the motions of stent grafts in AAA. Secondly, multiple methods to segment the stent graft from these data are discussed. Thirdly, this work proposes a method that uses image registration to apply motion to the segmented stent mode
    • …
    corecore