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Completed master theses

[1]
Q. Cao, "Automatic Segmentation Using 3DVolumes of the Nerve Fiber Layer Waist at the Optic Nerve Head," , 2024.
[2]
A. Mohamed, "Comparing Shear Wave Elastography and Magnetic Resonance Elastography for Assessing the Levator Ani Muscle," , 2024.
[3]
A. Franke and T. Hanna, "Database solutions suitable for XAI cardiovascular disease predictions," , 2024.
[4]
P. Hosseiniakram, "Development of a Novel Force-Sensing Attachment Device for Enhanced Accuracy in Pediatric Ultrasound-Guided Procedures," , 2024.
[5]
A. Hopkins, "Scatter Correction in PET Imaging," , 2024.
[6]
A. Adelöw, "Transformer-Based Learned Primal-Dual Reconstruction for PET," , 2024.
[7]
J. Wang, "Utilizing Image Processing Techniques and Generative Adversarial Networks to Bridge the Quality Gap in Low-Frequency Ultrasound Imaging," , 2024.
[8]
A. Horsma, "Verification of Transverse Doppler-Ultrasound for Assessment of Blood Flow Velocity," , 2024.
[9]
B. Koxha and M. Jova Martinez, "Anisotropic Muscle Phantoms for Shear Wave Elastography Assessment of the Levator Ani Muscle Properties," , 2023.
[10]
X. Wan, "Assessing the Streamline Plausibility Through Convex Optimization for Microstructure Informed Tractography(COMMIT) with Deep Learning," , 2023.
[11]
D. Borghäll, "Automatic event detection oncontinuous glucose datausing neural networks," , 2023.
[12]
T. Proudhon, "Domain Adaptation for Multi-Contrast Image Segmentation in Cardiac Magnetic Resonance Imaging," , 2023.
[13]
T. Pstrusiński, "Impact of the autoencoder-based FINTA tractogram filtering method on brain networks in subjects with Mild Cognitive Impairment," , 2023.
[14]
S. Bonato, "Optic nerve sheath diameter semantic segmentation and feature extraction," , 2023.
[15]
Y. Zheng, "Predictive MR Image Generation for Alzheimer’s Disease and Normal Aging Using Diffeomorphic Registration," , 2023.
[16]
N. Lindström Söraas, "Respiratory Motion Correction in PET Imaging: Comparative Analysis of External Device and Data-driven Gating Approaches," , 2023.
[17]
B. Jefford-Baker, "Autonomous Patient Monitoring in the Intermediate Care Unit by Live Video Analysis," , 2022.
[18]
Z. Shuli, "Coronary Artery Plaque Segmentation with CTA Images Based on Deep Learning," , 2022.
[19]
K. Yara, "Implementation of Super-Resolution Ultrasound Imaging for in Vitro Experiments," , 2022.
[20]
P. Meyrat, "Spatiotemporal PET reconstruction with Learned Registration," , 2022.
[21]
Y. Zhou, "Synthesis of Pediatric Brain Tumor Image With Mass Effect," , 2022.
[22]
E. Bengtsdotter, "Towards Anatomically Plausible Streamline Tractography with Deep Reinforcement Learning," , 2022.
[23]
I. Johansson, "Ultrasound Imaging Velocimetry using Polyvinyl Alcohol Shelled Microbubbles," , 2022.
[24]
L. Hugo, "Characterization of Center-of-Mass and Rebinning in Positron Emission Tomography with Motion," , 2021.
[25]
M. Pop, "Development of patient-specific fetal head phantom for experimental evaluation of vacuum assisted delivery," , 2021.
[26]
Y. Levin, "Finite Element Head ModelPersonalization by Mesh Morphing," , 2021.
[27]
L. Xu, "GAN-based Automatic Segmentation of Thoracic Aorta from Non-contrast-Enhanced CT Images," , 2021.
[28]
M. Kim, "Improving Knee Cartilage Segmentation using Deep Learning-based Super-Resolution Methods," , 2021.
[29]
G. Norman, "A Segmentation Network with a Class-Agnostic Loss Function for Training on Incomplete Data," , 2020.
[30]
E. Lindroth, "Acoustic Characterization of the Cellulose-coated Perfluorocarbon Droplets based on Phase Velocity Measurements," , 2020.
[31]
L. Saljén, "Acoustic Characterization of the Frequency-Dependent Attenuation Profile of Cellulose Stabilized Perfluorocarbon Droplets," , 2020.
[32]
S. Öquist, "Acoustic Droplet Vaporization : An Assessment of How Ultrasound Wave Parameters Influence the Vaporization Efficiency," , 2020.
[33]
J. Stoor, "An Analysis of Context Channel Integration Strategies for Deep Learning-Based Medical Image Segmentation," , 2020.
[34]
A. Guazzo, "Deep Learning for PET Imaging : From Denoising to Learned Primal-Dual Reconstruction," , 2020.
[35]
S. Hägglund, "Development of a Tool for Imaging the Pumping-Out Behavior of Poly- Vinyl Alcohol Shelled Microbubbles," , 2020.
[36]
M. Köpff, "Impact of tractogram filtering and graph creation for structural connectomics in subjects with mild cognitive impairment," , 2020.
[37]
M. Ahmed, "Medical Image Segmentation using Attention-Based Deep Neural Networks," , 2020.
[38]
D. Nimander, "Acoustic Droplet Vaporization of Perfluorocarbon Filled Microdroplets," , 2019.
[39]
N. Agerskov, "Adaptable Semi-Automated 3D Segmentation Using Deep Learning with Spatial Slice Propagation," , 2019.
[40]
A. Savva, "Assessment of Functional Connectivity Impairment in Rat Brains," , 2019.
[41]
L. Rane and H. Runeskog, "Calculating Center of Mass Using List Mode Data from PET Biograph128 mCT-1104," , 2019.
[42]
Y. Chen, "Classification of Atypical Femur Fracture with Deep Neural Networks," , 2019.
[43]
J. Lindemalm Karlsson, "Deep Learning-Based Automated Segmentation and Detection of Chondral Lesions on the Distal Femur," , 2019.
[44]
I. Gouwy, "Development of Ultrasound Pulse Sequences for Acoustic Droplet Vaporization," , 2019.
[45]
P. Rahgozar, "Evaluation of a Radiomics Model for Classification of Lung Nodules," , 2019.
[46]
T. BINDER, "Gland Segmentation with Convolutional Neural Networks : Validity of Stroma Segmentation as a General Approach," , 2019.
[47]
W. Löffler, "Non-destructive Evaluation of Ultrasound Contrast Agent," , 2019.
[48]
G. Söderström, "Regional MRI T1 mapping analysis of tobacco smoke exposed mouse lungs," , 2019.
[49]
E. Massai, "A Machine Learning Approach for Better Understanding the Neuromodulation of Locomotion," , 2018.
[50]
J. S. L. Vidmark, "An investigation of the relationships between electrotactile stimulus parameters, primary afferent response, and perceived sensation," , 2018.