Paul Stöwer

1 to 6 of 23

20NOV 2024
Ph.D. Gallery
Paula Andrea Pérez-Toro
Acoustic and Linguistic Analysis in Neurological and Psychiatric Disorders This thesis investigates the application of speech and language analysis for clinical evaluation and monitoring of neurological and psychiatric disorders, specifically Major Depression Disorder (MDD), Alzheimer’s Disease (AD), and Parkinson’s Disease (PD). Given the symptomatic overlap and diagnostic challenges presented by these conditions, this thesis uses […]Acoustic and Linguistic Analysis in Neurological and Psychiatric Disorders This thesis investigates the application of speech and language analysis for clinical evaluation and monitoring of neurological and psychiatric disorders, specifically Major Depression Disorder (MDD), Alzheimer’s Disease (AD), and Parkinson’s Disease (PD). Given the symptomatic overlap and diagnostic challenges presented by these conditions, this thesis uses […]
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20NOV 2024
Ph.D. Gallery
Julia Schottenhamml
A.Eye: Enhancing OCT and OCTA through Machine Learning Techniques
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05JUN 2024
Ph.D. Gallery
Philipp Klumpp
Phonetic Transfer Learning from Healthy References for the Analysis of Pathological Speech Automatic speech recognition (ASR) experienced a major leap forward through many advances in deep machine learning over the past decade. In each new iteration of neural ASR architecture, the increase in performance was accompanied by an increasing number of model parameters. Speech recognizers […]
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05JUN 2024
Ph.D. Gallery
Sebastian Bayerl
Machine Learning for Stuttering Detection and Classification in Stuttering Therapy
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05JUN 2024
Ph.D. Gallery
Fabian Wagner
Hybrid Machine Learning Approaches for Image Reconstruction and Processing in Low-Dose Computed Tomography Diagnostic decisions in clinical workflows often hinge on the interpretation of medical images. The inherent quality of these images plays a critical role in discerning relevant anatomical and pathological features. Factors such as radiation exposure, acquisition duration, and patient motion directly influence […]Hybrid Machine Learning Approaches for Image Reconstruction and Processing in Low-Dose Computed Tomography Diagnostic decisions in clinical workflows often hinge on the interpretation of medical images. The inherent quality of these images plays a critical role in discerning relevant anatomical and pathological features. Factors such as radiation exposure, acquisition duration, and patient motion directly influence […]
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25JAN 2024
Ph.D. Gallery
Felix Denzinger
Deep Learning-based Grading of Coronary Artery Disease from Coronary CT Angiography Scans One of the deadliest disease types in modern societies is coronary artery disease (CAD). It is often related to coronary artery plaques aggregating within the vessel wall obstructing the lumen causing a stenosis. To support physicians this thesis aims to answer the following […]
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