In this lecture the basic background of Radiooncology for Medical Physics will be covered. The lecture will be held at the Pius-Hospital Oldenburg in several blocks. Detailed schedule will be announced in May,
Die Studierenden erlangen fundierte Kenntnisse in der biomedizinischen Physik mit Überblick über die (Neuro)-Physiologie, erwerben Fertigkeiten zur selbständigen Vertiefung diese Fachkenntnisse und erwerben Kompetenzen für eine Anwendung dieser Fachkenntnisse im Rahmen von Facharbeiten und Projekten in verschiedenen Bereichen der Neurosensorik.
Inhalte:
Anatomie, Physiologie und Pathophysiologie des Zentralen Nervensystems, Physiologie von Neuronen, Neuronenmodelle, Modelle von Neuronenverbänden und neuronaler Netze, Neuronale Kodierung und Merkmalsextraktion, Neurosensorik (Methoden, Experimente und Modelle neurosensorischer Verarbeitung), Neurokognition (Methoden, Experimente und Modelle neuronaler Verarbeitung bei kognitiven Funktionen), höhere Hirnfunktionen (Handlungssteuerung, Emotionen,...) , aktuelle Forschungsansätze in der Neurokognition aus Sicht der Physik.
Aktuelle Forschungsarbeiten aus folgenden Gebieten der Signal- und Sprachverarbeitung: Ein- und mehrkanalige Sprachverbesserung, Sensornetzwerke, Sprachmodellierung, Sprachtechnologie, Signalverarbeitung für Hörgeräte und Multimedia.
The students will learn the current research directions and challenges of the Machine Learning research field. By presenting examples from Machine Learning algorithms applied to sensory data tasks including task in Computer Hearing and Computer Vision the students will be taught the current strengths and weaknesses of different approaches. The presentations of current research papers by the participants will make use of computers and projectors. Programming examples and animations will be used to support the interactive component of the presentations. In scientific discussions of the presented and related work, the students will deepen their knowledge about current limitations of Machine Learning approaches both on the theoretical side and on the side of their technical and practical realizations. Presentations of interdisciplinary research will enable the students to carry over their Machine Learning knowledge to address questions in other scientific domains.
Contents:
Building up on advanced Machine Learning knowledge, this seminar discusses recent scientific contributions and developments in Machine Learning as well as recent papers on applications of Machine Learning algorithms. Typical application domains include general pattern recognition, computer hearing, computer vision and computational neuroscience. Typical tasks include auditory and visual signal enhancements, source separation, auditory and visual object learning and recognition, auditory scene analysis, data compression and inpainting. Applications to computational neuroscience will discuss recent papers on the probabilistic interpretation of neural learning and biological intelligence.
Aktuelle Forschungsarbeiten aus folgenden Gebieten der medizinischen Physik; Signalverarbeitung und Akustik:
Audiologie, Neurosensorik (EEG,MEG, fMRI, OAE,…), Psychoakustik, Sprachakustik, Sprachtechnologie, Signalverarbeitung für Hörgeräte und Multimedia
One or two examinations depending on selected courses
Learning outcomes/competencies
The aim of this module is to provide the students with access to 3CP courses in the area of biomedical physics and acoustics, which address the specific interests of the students and offer either unique in-depth knowledge or the opportunity to develop specific engineering skills. Through this module, the students acquire advanced knowledge and engineering skills in the area of biomedical physics and acoustics.