Lecture

Until further notice, this course will take place in electronic form. Detailed information is provided in the StudOn-course "Visual Computing in Medicine 2 (VCMed 2) - summer term 2020".
Bis auf Weiteres findet der Kurs in elektronischer Form statt. Weitere Informationen finden Sie im StudOn-Kurs "Visual Computing in Medicine 2 (VCMed 2) - summer term 2020".

Contents

Building onto the lecture VCMed1, VCMed2 provides examples of concrete solutions for diagnosis and therapy planning based on complex clinical images. It provides information how basic methods are selected and combined into practical applicable concepts. Examples from clinical applications will be used to relate strategies and requirements in clinical practice as well as the development process. Additionally, methods of medical image analysis and visualization are discussed in detail.

Linking methods of medical image analysis and visualization for processing diagostic and interventional questions
Providing algorithmic approaches with concrete solution strategies for the processing of clinical iamges from the perspective of medical needs
Overview of various medical imaging domains
Multimodal image registration with non-rigid transformations
Current topics of image-based diagnosis and therapy planning

Recommended literature

P.M. Schlag, S. Eulenstein, Th. Lange „Computerassistierte Chirurgie", Elsevier Verlag 2010
H. Handels, „Medizinische Bildverarbeitung, Bildanalyse, Mustererkennung und Visualisierung für die computergestützte ärztliche Diagnostik und Therapie", Vieweg und Teubner Verlag, 2009
B. Preim, D. Bartz, "Visualization in Medicine - Theory, Algorithms, and Applications”, Morgan Kaufmann Verlag, 2007
E. Neri, D. Caramella, C. Bartolozzi, „Image Processing in Radiology", Springer Verlag, 2008
Th. Lehmann, W. Oberschelp, E. Pelikan, R. Pepges, „Bildverarbeitung für die Medizin", Springer Verlag, 1997

ECTS information:

Title:

Visual Computing in Medicine 2

Credits: 2,5

Contents

Based on VCMed1 the lecture VCMed2 discusses practical approaches for the diagnosis and therapy planning of complex diseases. It will be shown how fundamental methods are selected and integrated to practically applicable concepts. Examples demonstrate the relation to strategies and requirements in clinical practice and the industrial development process. Additionally, complex methods of medical image analysis and visualization will be explained.

Combination of methods for medical image analysis and visualization in order to treat cardiological, neurological, oncological problems
Complex approaches with precise strategies for the processing of important disease patterns form a medical application point of view
Software development process from industrial point of view
Overview of complex disease patterns
Multimodal image registration with nonlinear transformations
Current topics of image based diagnosis and therapy planning
Practical demonstrations in the labs and in the clinics

Literature

P.M. Schlag, S. Eulenstein, Th. Lange „Computerassistierte Chirurgie", Elsevier Verlag 2010
H. Handels, „Medizinische Bildverarbeitung, Bildanalyse, Mustererkennung und Visualisierung für die computergestützte ärztliche Diagnostik und Therapie", Vieweg und Teubner Verlag, 2009
B. Preim, D. Bartz, "Visualization in Medicine - Theory, Algorithms, and Applications”, Morgan Kaufmann Verlag, 2007
E. Neri, D. Caramella, C. Bartolozzi, „Image Processing in Radiology", Springer Verlag, 2008
Th. Lehmann, W. Oberschelp, E. Pelikan, R. Pepges, „Bildverarbeitung für die Medizin", Springer Verlag, 1997

Additional information

Expected participants: 45, Maximale Teilnehmerzahl: 50

Verwendung in folgenden UnivIS-Modulen

Startsemester WS 2021/2022:: Visual Computing in Medicine (VCMed)



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