Ph.D. Gallery

Browse all posts in the Ph.D. Gallery category.

7 to 12 of 106

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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15DEC 2023
Ph.D. Gallery
Felix Meister
Deep Learning and Computational Modeling of Physiology Deep Learning (DL) and computational modeling (CM) could revolutionize the healthcare system by personalizing therapies to patients and enabling precision medicine (PM). While DL can automatically extract decision rules from large amounts of data, CM leverages known principles from physics and physiology to provide mechanistic insights into biophysical […]Deep Learning and Computational Modeling of Physiology Deep Learning (DL) and computational modeling (CM) could revolutionize the healthcare system by personalizing therapies to patients and enabling precision medicine (PM). While DL can automatically extract decision rules from large amounts of data, CM leverages known principles from physics and physiology to provide mechanistic insights into biophysical […]
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15DEC 2023
Ph.D. Gallery
Lukas Folle
Data-Driven Derivation of Rheumatological Disease Characteristics from Medical Images Rheumatologists have various tools at hand that allow characterizing the diseases of their patients. A multitude of those tools requires human annotation, which in some cases is time-intensive and error-prone. This poses a unique challenge, that can be addressed by modern pattern recognition advancements. In this […]Data-Driven Derivation of Rheumatological Disease Characteristics from Medical Images Rheumatologists have various tools at hand that allow characterizing the diseases of their patients. A multitude of those tools requires human annotation, which in some cases is time-intensive and error-prone. This poses a unique challenge, that can be addressed by modern pattern recognition advancements. In this […]
Read more about Lukas Folle
30OCT 2023
Ph.D. Gallery
Florian Thamm
Deep Learning and Image Processing for Stroke Diagnosis with Computed Tomography Angiography Computed Tomography (CT) is an effective tool, especially in acute situations, which contributes significantly to diagnosing a wide variety of clinical pictures. This includes, with a high prevalence, ischemic stroke, in which an oxygen deficiency is caused by the occlusion of a vessel, […]
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19SEP 2023
Ph.D. Gallery
Christian Bergler
Deep Learning Applied to Animal Linguistics Even nowadays, people have only a very limited understanding about animal communication. Scientists are still far from identifying statistically relevant, animal-specific, and recurring linguistic paradigms. However, combined with the associated situation-specific behavioral observations, these patterns represent an indispensable basis for decoding animal communication. In order to derive statistically significant […]Deep Learning Applied to Animal Linguistics Even nowadays, people have only a very limited understanding about animal communication. Scientists are still far from identifying statistically relevant, animal-specific, and recurring linguistic paradigms. However, combined with the associated situation-specific behavioral observations, these patterns represent an indispensable basis for decoding animal communication. In order to derive statistically significant […]
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19SEP 2023
Ph.D. Gallery
Sebastian Gündel
Recognition of Similarities and Abnormalities in Chest Radiographs In a medical sense, radiography is an imaging technique to produce a plain image of the human body. Radiography of the chest is the most commonly used medical image acquisition method. In contrast to other imaging techniques, radiography benefits from fast examination procedures and low radiation doses. […]
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