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Visar resultat 1 - 5 av 9 uppsatser som matchar ovanstående sökkriterier.
1. Anatomical segmentation of the human brain: comparative assessment of two automatic methods
Master-uppsats,Sammanfattning : Magnetic Resonance Imaging (MRI) is a robust and versatile imaging modality and an integral component of a lot of studies, especially when performing quantitative analysis. MRI is the preferred method of imaging the brain because of its excellent soft tissue contrast. LÄS MER
2. Predictive MR Image Generation for Alzheimer’s Disease and Normal Aging Using Diffeomorphic Registration
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Alzheimer´s Disease (AD) is the most prevalent cause of dementia, signifying a progressive and degenerative brain disorder that causes cognitive function deterioration including memory loss, communication difficulties, impaired judgment, and changes in behavior and personality. Compared to normal aging, AD introduces more profound cognitive impairments and brain morphology changes. LÄS MER
3. ATLAS-BASED SEGMENTATION OF ULTRAHIGH-RESOLUTION STRUCTURAL MR HEAD IMAGES ACQUIRED AT 7 TESLA
Master-uppsats,Sammanfattning : Purpose: The purpose of this work was to find out how the existing brain atlases and segmentation algorithms perform when applied to ultrahigh-resolution MR brain images, acquired with a 7-Tesla scanner. Also to make adaptations to deal with the potential challenges and evaluate the quality of the anatomical segmentations of the 7- Tesla images. LÄS MER
4. Visual Transformers for 3D Medical Images Classification: Use-Case Neurodegenerative Disorders
Master-uppsats, Högskolan i Halmstad/Akademin för informationsteknologiSammanfattning : A Neurodegenerative Disease (ND) is progressive damage to brain neurons, which the human body cannot repair or replace. The well-known examples of such conditions are Dementia and Alzheimer’s Disease (AD), which affect millions of lives each year. LÄS MER
5. Characterization of discrepancies between manual and automatic segmentation to improve anatomical brain atlases
Master-uppsats,Sammanfattning : Purpose: To characterize discrepancies between expert manually segmented brain images from Hammers Atlas Database and automatically generated segmentations of the same images; to decide whether they can be attributed to flaws in the automatic segmentation or in the manual segmentation; and to determine general rules that enable these decisions. Theory: Image segmentation plays an important role in clinical neuroscience and experimental medicine for extraction of information from medical images, and it is a fundamental image processing step in medical image analysis. LÄS MER