Essays about: "Atlas-based segmentation"
Showing result 1 - 5 of 12 essays containing the words Atlas-based segmentation.
-
1. Volumetric Image Segmentation of Lizard Brains
University essay from KTH/Tillämpad fysikAbstract : Accurate measurement brain region volumes are important in studying brain plasticity, which brings insight into the fundamental mechanisms in animal, memory, cognitive, and behavior research. The traditional methods of brain volume measurements are ellipsoid or histology. READ MORE
-
2. ATLAS-BASED SEGMENTATION OF ULTRAHIGH-RESOLUTION STRUCTURAL MR HEAD IMAGES ACQUIRED AT 7 TESLA
University essay fromAbstract : 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. READ MORE
-
3. Using Deep Learning to SegmentCardiovascular 4D Flow MRI : 3D U-Net for cardiovascular 4D flow MRI segmentation and Bayesian 3D U-Net for uncertainty estimation
University essay from Linköpings universitet/Institutionen för datavetenskapAbstract : Deep convolutional neural networks (CNN’s) have achieved state-of-the-art accuraciesfor multi-class segmentation in biomedical image science. In this thesis, A 3D U-Net isused to segment 4D flow Magnetic Resonance Images that include the heart and its largevessels. READ MORE
-
4. Similarity models for atlas-based segmentation of whole-body MRI volumes
University essay from Linköpings universitet/Institutionen för medicinsk teknikAbstract : In order to analyse body composition of MRI (Magnetic Resonance Imaging) volumes, atlas-based segmentation is often used to retrieve information from specific organs or anatomical regions. The method behind this technique is to use an already segmented image volume, an atlas, to segment a target image volume by registering the volumes to each other. READ MORE
-
5. Evaluating Segmentation of MR Volumes Using Predictive Models and Machine Learning
University essay from Linköpings universitet/Institutionen för medicinsk teknikAbstract : A reliable evaluation system is essential for every automatic process. While techniques for automatic segmentation of images have been extensively researched in recent years, evaluation of the same has not received an equal amount of attention. READ MORE
