Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 50 for “"Magnetic Resonance Images"”.
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Segmentation of brain tissue from magnetic resonance images
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.
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Automatic segmentation of magnetic resonance images of the brain
Magnetic resonance imaging (MRI) is a technique used primarily in medical settings to produce high quality images of the human body’s internal anatomy. Each image is of a thin slice through the body, with the typical distance between slices being a few millimeters. Brain segmentation is the …
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Analysis of trabecular bone mechanical properties from magnetic resonance images
… particularly computed tomography (CT) and magnetic resonance (MR) imaging, allowed the generation of three-dimensional (3D) images for the morphological analysis of trabecular bone. Furthermore, the 3D image data can be the source of finite element (FE) models. FE analysis of such data …
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Deep Learning Methods for Muscle Analysis From Magnetic Resonance Images
… in segmenting skeletal muscles from anisotropic magnetic resonance imaging (MRI) scans and concluded that the hybrid model demonstrated the best performance. This finding is used in the second study, where a novel hybrid model is proposed. It also demonstrated human-level performance on isotropic …
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AM-FM Analysis of Structural and Functional Magnetic Resonance Images
… Frequency-Modulation (AM-FM) methods to magnetic resonance images (MRI). The basic goal is to provide a framework for exploring non-stationary characteristics of structural and functional MRI (sMRI and fMRI). First, we provide a comparison framework for the most popular AM-FM methods …
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Population-wise consistent segmentation of diffusion weighted magnetic resonance images
… construct anatomical atlases and segment medical images. We propose an integrated registration and clustering algorithm to compute an anatomical atlas of fiber-bundles as well as deep gray matter structures from a population of diffusion tensor MR images (DT-MRI). We refer to this algorithm as …
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A 3D Framework for the Musculoskeletal Segmentation of Magnetic Resonance Images
In this thesis a new framework is proposed for obtaining the spongy bone, cortical bone, muscle and adipose tissue from MRI data. The method focuses on the accurate extraction of the edges of the target tissues, which is the main drawback of previous works. In this framework six new methods, as …
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Predicting learning success from patterns of pre-training magnetic resonance images
… learning from time-averaged T2*-weighted images, a follow-up experiment was designed and performed with additional magnetic resonance (MR) measurements, including susceptibility-sensitive ones, such as susceptibility-weighted imaging (SWI), T2-, T2*-quantitative as well as diffusion tensor …
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Efficient automatic correction and segmentation based 3D visualization of magnetic resonance images
In the recent years, the demand for automated processing techniques for digital medical image volumes has increased substantially. Existing algorithms, however, still often require manual interaction, and newly developed automated techniques are often intended for a narrow segment of processing …
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Identifying lesions in paediatric epilepsy using morphometric and textural analysis of magnetic resonance images
We develop an image processing pipeline on Magnetic Resonance Imaging (MRI) sequences to identify features of Focal Cortical Dysplasia (FCD) in patients with MRIvisible FCD. We aim to use a computer-aided diagnosis system to identify epileptogenic lesions with a combination of established …
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Automated detection of multiple sclerosis lesions in magnetic resonance images of the human brain
Magnetic resonance (MR) imaging is a medical technique which permits the visualization of a variety of tumors, lesions, and abnormalities present within the soft biological tissues of the body. Segmentation of medical image data is the process of assigning anatomically-meaningful labels to each …
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Rigid registration of Echoplanar and conventional magnetic resonance images by minimizing the Kullback-Leibler distance
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.
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Performance analysis of automatic techniques for tissue classification in magnetic resonance images of the human brain
Classification of Magnetic Resonance (MR) images of the human brain into anatomically meaningful tissue labels is an important processing step in many research and clinical studies in neurology. The medical imaging research community is presented with a wide choice of classification algorithms from …
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Quantitative analysis of intro-operative magnetic resonance images and tissue survival for laserthermia of 9L gliosarcoma
Thesis (Nucl. E.)--Massachusetts Institute of Technology, Dept. of Nuclear Engineering, 1994.
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A Machine Learning and Computer Assisted Methodology for Diagnosing Chronic Lower Back Pain on Lumbar Spine Magnetic Resonance Images
… time for a specialist appointment, time for a Magnetic Resonance Imaging (MRI) scan and time for the analysis result to come out. Currently diagnosing the lower back pain is done by visual observation and analysis of the lumbar spine MRI images by radiologists and clinicians and this process …
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De-noising of Real-time Dynamic Magnetic Resonance Images by the Combined Application of Karhunen-Loeve Transform (KLT) and Wavelet Filtering
… is presented to de-noise dynamic cardiac magnetic resonance images that simultaneously takes advantage of the intrinsic spatial and temporal redundancies of real-time cardiac cine. This new image filtering technique combines two well-established methods: temporal Karhunen-Loeve transform …
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An automated classification system to determine malignant grades of brain tumour (glioma) in magnetic resonance images based on meta-trainable multiple classifier schemes
… measure of the brain tumour descriptors in MR images lead to an accurate classification of malignant brain tumours. This work starts from the standpoint that meta-trainable fusion of multiple classifier models can offer a better classification accuracy to recognise the malignant grade of glioma …
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Decompressive craniectomy in children with traumatic brain injury
… evidence from diverse studies that use data from magnetic resonance images, cerebral owygenation and cerebral blood flow measurements have highlighted potential adverse effects that may occur with these therapies.
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Exploring the range of motion between the acetabular component and the femoral component in hip resurfacing
… premature component failure. Currently, magnetic resonance images and anterior-posterior radiographs are commonly used to diagnose and assess pathological conditions of the hip that may require a hip resurfacing arthroplasty...The main objective of this study was to investigate the use of …
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Computational biomechanics in the remodelling rat heart post myocardial infarction
… rat heart geometries were developed from cardiac magnetic resonance images of a healthy heart and a heart with left ventricular (LV) infarction two weeks and four weeks after infarct induction. From these geometries, FE models were established. To represent the myocardium, a structure-based …
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