Search result: Catalogue data in Spring Semester 2018

Biomedical Engineering Master Information
Major Courses
Bioimaging
Recommended Elective Courses
These courses are particularly recommended for the Bioimaging track. Please consult your track adviser if you wish to select other subjects.
NumberTitleTypeECTSHoursLecturers
227-0967-00LComputational Neuroimaging Clinic Information W3 credits2VK. Stephan
AbstractThis seminar teaches problem solving skills for computational neuroimaging, based on joint analyses of neuroimaging and behavioural data. It deals with a wide variety of real-life problems that are brought to this meeting from the neuroimaging community at Zurich, e.g. mass-univariate and multivariate analyses of fMRI/EEG data, or generative models of fMRI, EEG, or behavioural data.
Objective1. Consolidation of theoretical knowledge (obtained in one of the following courses: 'Methods & models for fMRI data analysis', 'Translational Neuromodeling', 'Computational Psychiatry') in a practical setting.
2. Acquisition of practical problem solving strategies for computational modeling of neuroimaging data.
ContentThis seminar teaches problem solving skills for computational neuroimaging, based on joint analyses of neuroimaging and behavioural data. It deals with a wide variety of real-life problems that are brought to this meeting from the neuroimaging community at Zurich, e.g. mass-univariate and multivariate analyses of fMRI/EEG data, or generative models of fMRI, EEG, or behavioural data.
.
Prerequisites / NoticeThe participants are expected to have successfully completed at least one of the following courses:
'Methods & models for fMRI data analysis',
'Translational Neuromodeling',
'Computational Psychiatry'
151-0622-00LMeasuring on the Nanometer ScaleW2 credits2GA. Stemmer, T. Wagner
AbstractIntroduction to theory and practical application of measuring techniques suitable for the nano domain.
ObjectiveIntroduction to theory and practical application of measuring techniques suitable for the nano domain.
ContentConventional techniques to analyze nano structures using photons and electrons: light microscopy with dark field and differential interference contrast; scanning electron microscopy, transmission electron microscopy. Interferometric and other techniques to measure distances. Optical traps. Foundations of scanning probe microscopy: tunneling, atomic force, optical near-field. Interactions between specimen and probe. Current trends, including spectroscopy of material parameters.
Lecture notesClass notes and special papers will be distributed.
227-0125-00LOptics and PhotonicsW6 credits2V + 2UJ. Leuthold
AbstractThis lecture covers both - the fundamentals of "Optics" such as e.g. "ray optics", "coherence", the "Planck law" or the "Einstein relations" but also the fundamentals of "Photonics" on the generation, processing, transmission and detection of photons.
ObjectiveA sound base for work in the field of optics and photonics will be given.
ContentChapter 1: Ray Optics
Chapter 2: Electromagnetic Optics
Chapter 3: Polarization
Chapter 4: Coherence and Interference
Chapter 5: Fourier Optics and Diffraction
Chapter 6: Guided Wave Optics
Chapter 7: Optical Fibers
Chapter 8: The Laser
Lecture notesLecture notes will be handed out.
Prerequisites / NoticeFundamentals of Electromagnetic Fields (Maxwell Equations) & Bachelor Lectures on Physics.
227-0384-00LUltrasound Fundamentals, Imaging, and Medical Applications Restricted registration - show details
Number of participants limited to 25.
W4 credits3GO. Göksel
AbstractUltrasound is the only imaging modality that is nonionizing (safe), real-time, cost-effective, and portable, with many medical uses in diagnosis, intervention guidance, surgical navigation, and as a therapeutic option. In this course, we introduce conventional and prospective applications of ultrasound, starting with the fundamentals of ultrasound physics and imaging.
ObjectiveStudents can use the fundamentals of ultrasound, to analyze and evaluate ultrasound imaging techniques and applications, in particular in the field of medicine, as well as to design and implement basic applications.
ContentUltrasound is used in wide range of products, from car parking sensors, to assessing fault lines in tram wheels. Medical imaging is the eye of the doctor into body; and ultrasound is the only imaging modality that is nonionizing (safe), real-time, cheap, and portable. Some of its medical uses include diagnosing breast and prostate cancer, guiding needle insertions/biopsies, screening for fetal anomalies, and monitoring cardiac arrhythmias. Ultrasound physically interacts with the tissue, and thus can also be used therapeutically, e.g., to deliver heat to treat tumors, break kidney stones, and targeted drug delivery. Recent years have seen several novel ultrasound techniques and applications – with many more waiting in the horizon to be discovered.

This course covers ultrasonic equipment, physics of wave propagation, numerical methods for its simulation, image generation, beamforming (basic delay-and-sum and advanced methods), transducers (phased-, linear-, convex-arrays), near- and far-field effect, imaging modes (e.g., A-, M-, B-mode), Doppler and harmonic imaging, ultrasound signal processing techniques (e.g., filtering, time-gain-compensation, displacement tracking), image analysis techniques (deconvolution, real-time processing, tracking, segmentation, computer-assisted interventions), acoustic-radiation force, plane-wave imaging, contrast agents, micro-bubbles, elastography, biomechanical characterization, high-intensity focused ultrasound and therapy, lithotripsy, histotripsy, photo-acoustics phenomenon and opto-acoustic imaging, as well as sample non-medical applications such as the basics of non-destructive testing (NDT).
Prerequisites / NoticeHands-on exercises will help apply concepts learned in the module, and will involve a mix of designing, implementing, and evaluating in simulation environments, such as Matlab FieldII and k-Wave toolboxes.

Prerequisites: Familiarity with basic numerical methods.
Basic programming skills and experience in Matlab.
227-0390-00LElements of MicroscopyW4 credits3GM. Stampanoni, G. Csúcs, A. Sologubenko
AbstractThe lecture reviews the basics of microscopy by discussing wave propagation, diffraction phenomena and aberrations. It gives the basics of light microscopy, introducing fluorescence, wide-field, confocal and multiphoton imaging. It further covers 3D electron microscopy and 3D X-ray tomographic micro and nanoimaging.
ObjectiveSolid introduction to the basics of microscopy, either with visible light, electrons or X-rays.
ContentIt would be impossible to imagine any scientific activities without the help of microscopy. Nowadays, scientists can count on very powerful instruments that allow investigating sample down to the atomic level.
The lecture includes a general introduction to the principles of microscopy, from wave physics to image formation. It provides the physical and engineering basics to understand visible light, electron and X-ray microscopy.
During selected exercises in the lab, several sophisticated instrument will be explained and their capabilities demonstrated.
LiteratureAvailable Online.
227-0391-00LMedical Image Analysis
Basic knowledge of computer vision would be helpful.
W3 credits2GE. Konukoglu, P. C. Cattin, M. A. Reyes Aguirre
AbstractIt is the objective of this lecture to introduce the basic concepts used
in Medical Image Analysis. In particular the lecture focuses on shape
representation schemes, segmentation techniques, machine learning based predictive models and various image registration methods commonly used in Medical Image Analysis applications.
ObjectiveThis lecture aims to give an overview of the basic concepts of Medical Image Analysis and its application areas.
Prerequisites / NoticePrerequisites:
Basic concepts of mathematical analysis and linear algebra.

Preferred:
Basic knowledge of computer vision and machine learning would be helpful.

The course will be held in English.
227-0396-00LEXCITE Interdisciplinary Summer School on Bio-Medical Imaging Information Restricted registration - show details
The school admits 60 MSc or PhD students with backgrounds in biology, chemistry, mathematics, physics, computer science or engineering based on a selection process.

Students have to apply for acceptance by April 23, 2018. To apply a curriculum vitae and an application letter need to be submitted. The notification of acceptance will be given by May 25, 2018. Further information can be found at: Link.
W4 credits6GS. Kozerke, G. Csúcs, J. Klohs-Füchtemeier, S. F. Noerrelykke, M. P. Wolf
AbstractTwo-week summer school organized by EXCITE (Center for EXperimental & Clinical Imaging TEchnologies Zurich) on biological and medical imaging. The course covers X-ray imaging, magnetic resonance imaging, nuclear imaging, ultrasound imaging, infrared and optical microscopy, electron microscopy, image processing and analysis.
ObjectiveStudents understand basic concepts and implementations of biological and medical imaging. Based on relative advantages and limitations of each method they can identify preferred procedures and applications. Common foundations and conceptual differences of the methods can be explained.
ContentTwo-week summer school on biological and medical imaging. The course covers concepts and implementations of X-ray imaging, magnetic resonance imaging, nuclear imaging, ultrasound imaging, infrared and optical microscopy and electron microscopy. Multi-modal and multi-scale imaging and supporting technologies such as image analysis and modeling are discussed. Dedicated modules for physical and life scientists taking into account the various backgrounds are offered.
Lecture notesHand-outs, Web links
Prerequisites / NoticeThe school admits 60 MSc or PhD students with backgrounds in biology, chemistry, mathematics, physics, computer science or engineering based on a selection process. To apply a curriculum vitae, a statement of purpose and applicants references need to be submitted. Further information can be found at: Link
227-0455-00LTerahertz: Technology & ApplicationsW4 credits6GK. Sankaran
AbstractThis block course will provide a solid foundation for understanding physical principles of THz applications. We will discuss various building blocks of THz technology - components dealing with generation, manipulation, and detection of THz electromagnetic radiation. We will introduce THz applications in the domain of imaging, communications, and energy harvesting.
ObjectiveThis is an introductory course on Terahertz (THz) technology and applications. Devices operating in THz frequency range (0.1 to 10 THz) have been increasingly studied in the recent years. Progress in nonlinear optical materials, ultrafast optical and electronic techniques has strengthened research in THz application developments. Due to unique interaction of THz waves with materials, applications with new capabilities can be developed. In theory, they can penetrate somewhat like X-rays, but are not considered harmful radiation, because THz energy level is low. They should be able to provide resolution as good as or better than magnetic resonance imaging (MRI), possibly with simpler equipment. Imaging, very-high bandwidth communication, and energy harvesting are the most widely explored THz application areas. We will study the basics of THz generation, manipulation, and detection. Our emphasis will be on the physical principles and applications of THz in the domain of imaging, communication and energy harvesting.

The second part of the block course will be a short project work related to the topics covered in the lecture. The learnings from the project work should be presented in the end.
ContentPART I:

- INTRODUCTION -
Chapter 1: Introduction to THz Physics
Chapter 2: Components of THz Technology

- THz TECHNOLOGY MODULES -
Chapter 3: THz Generation
Chapter 4: THz Detection
Chapter 5: THz Manipulation

- APPLICATIONS -
Chapter 6: THz Imaging
Chapter 7: THz Communication
Chapter 8: THz Energy Harvesting

PART 2:

- PROJECT WORK -
Short project work related to the topics covered in the lecture.
Short presentation of the learnings from the project work.
Full guidance and supervision will be given for successful completion of the short project work.
Lecture notesSoft-copy of lectures notes will be provided.
Literature- Yun-Shik Lee, Principles of Terahertz Science and Technology, Springer 2009
- Ali Rostami, Hassan Rasooli, and Hamed Baghban, Terahertz Technology: Fundamentals and Applications, Springer 2010
Prerequisites / NoticeGood foundation in electromagnetics is required.
Knowledge of microwave or optical communication is helpful, but not mandatory.
227-0966-00LQuantitative Big Imaging: From Images to StatisticsW4 credits2V + 1UK. S. Mader, M. Stampanoni
AbstractThe lecture focuses on the challenging task of extracting robust, quantitative metrics from imaging data and is intended to bridge the gap between pure signal processing and the experimental science of imaging. The course will focus on techniques, scalability, and science-driven analysis.
Objective1. Introduction of applied image processing for research science covering basic image processing, quantitative methods, and statistics.
2. Understanding of imaging as a means to accomplish a scientific goal.
3. Ability to apply quantitative methods to complex 3D data to determine the validity of a hypothesis
ContentImaging is a well established field and is rapidly growing as technological improvements push the limits of resolution in space, time, material and functional sensitivity. These improvements have meant bigger, more diverse datasets being acquired at an ever increasing rate. With methods varying from focused ion beams to X-rays to magnetic resonance, the sources for these images are exceptionally heterogeneous; however, the tools and techniques for processing these images and transforming them into quantitative, biologically or materially meaningful information are similar.
The course consists of equal parts theory and practical analysis of first synthetic and then real imaging datasets. Basic aspects of image processing are covered such as filtering, thresholding, and morphology. From these concepts a series of tools will be developed for analyzing arbitrary images in a very generic manner. Specifically a series of methods will be covered, e.g. characterizing shape, thickness, tortuosity, alignment, and spatial distribution of material features like pores. From these metrics the statistics aspect of the course will be developed where reproducibility, robustness, and sensitivity will be investigated in order to accurately determine the precision and accuracy of these quantitative measurements. A major emphasis of the course will be scalability and the tools of the 'Big Data' trend will be discussed and how cluster, cloud, and new high-performance large dataset techniques can be applied to analyze imaging datasets. In addition, given the importance of multi-scale systems, a data-management and analysis approach based on modern databases will be presented for storing complex hierarchical information in a flexible manner. Finally as a concluding project the students will apply the learned methods on real experimental data from the latest 3D experiments taken from either their own work / research or partnered with an experimental imaging group.
The course provides the necessary background to perform the quantitative evaluation of complicated 3D imaging data in a minimally subjective or arbitrary manner to answer questions coming from the fields of physics, biology, medicine, material science, and paleontology.
Lecture notesAvailable online.
LiteratureWill be indicated during the lecture.
Prerequisites / NoticeIdeally students will have some familiarity with basic manipulation and programming in languages like Matlab and R. Interested students who are worried about their skill level in this regard are encouraged to contact Kevin Mader directly (Link).

More advanced students who are familiar with Java, C++, and Python will have to opportunity to develop more of their own tools.
227-0973-00LTranslational Neuromodeling Information W6 credits4GK. Stephan
AbstractThis course provides a systematic introduction to Translational Neuromodeling (the development of mathematical models for diagnostics of brain diseases) and their application to concrete clinical questions (Computational Psychiatry/Psychosomatics). It focuses on a generative modeling strategy and discusses (hierarchical) Bayesian models of neuroimaging data and behaviour in detail.
ObjectiveTo obtain an understanding of the goals, concepts and methods of Translational Neuromodeling and Computational Psychiatry/Psychosomatics, particularly with regard to Bayesian models of neuroimaging (fMRI, EEG) and behavioural data.
ContentThis course provides a systematic introduction to Translational Neuromodeling (the development of mathematical models for diagnostics of brain diseases) and their application to concrete clinical questions (Computational Psychiatry/Psychosomatics). The first part of the course will introduce disease concepts from Psychiatry and Psychosomatics, their history, and clinical priority problems. The second part of the course concerns computational modeling of neuronal and cognitive processes for clinical applications. A particular focus is on Bayesian methods and generative models, e.g. dynamic causal models (DCMs) for inferring neuronal mechanisms from neuroimaging data, and hierarchical Bayesian models for inference on cognitive mechanisms from behavioural data. The course discusses the mathematical and statistical principles behind these models, illustrates their application to various psychiatric diseases, and outlines a general research strategy based on generative models.
In the practical exercises, students are asked to program their own generative model (in MATLAB) and use it for simulations and inference from real fMRI or behavioural data.
LiteratureSee TNU website:
Link
Prerequisites / NoticeBasic statistical knowledge, MATLAB programming skills
227-1034-00LComputational Vision (University of Zurich) Information
No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: INI402

Mind the enrolment deadlines at UZH:
Link
W6 credits2V + 1UD. Kiper, K. A. Martin
AbstractThis course focuses on neural computations that underlie visual perception. We study how visual signals are processed in the retina, LGN and visual cortex. We study the morpholgy and functional architecture of cortical circuits responsible for pattern, motion, color, and three-dimensional vision.
ObjectiveThis course considers the operation of circuits in the process of neural computations. The evolution of neural systems will be considered to demonstrate how neural structures and mechanisms are optimised for energy capture, transduction, transmission and representation of information. Canonical brain circuits will be described as models for the analysis of sensory information. The concept of receptive fields will be introduced and their role in coding spatial and temporal information will be considered. The constraints of the bandwidth of neural channels and the mechanisms of normalization by neural circuits will be discussed.
The visual system will form the basis of case studies in the computation of form, depth, and motion. The role of multiple channels and collective computations for object recognition will
be considered. Coordinate transformations of space and time by cortical and subcortical mechanisms will be analysed. The means by which sensory and motor systems are integrated to allow for adaptive behaviour will be considered.
ContentThis course considers the operation of circuits in the process of neural computations. The evolution of neural systems will be considered to demonstrate how neural structures and mechanisms are optimised for energy capture, transduction, transmission and representation of information. Canonical brain circuits will be described as models for the analysis of sensory information. The concept of receptive fields will be introduced and their role in coding spatial and temporal information will be considered. The constraints of the bandwidth of neural channels and the mechanisms of normalization by neural circuits will be discussed.
The visual system will form the basis of case studies in the computation of form, depth, and motion. The role of multiple channels and collective computations for object recognition will
be considered. Coordinate transformations of space and time by cortical and subcortical mechanisms will be analysed. The means by which sensory and motor systems are integrated to allow for adaptive behaviour will be considered.
LiteratureBooks: (recommended references, not required)
1. An Introduction to Natural Computation, D. Ballard (Bradford Books, MIT Press) 1997.
2. The Handbook of Brain Theorie and Neural Networks, M. Arbib (editor), (MIT Press) 1995.
376-1397-00LOrthopaedic BiomechanicsW4 credits3GR. Müller, G. H. Van Lenthe
AbstractThis course is aimed at studying the mechanical and structural engineering of the musculoskeletal system alongside the analysis and design of orthopaedic solutions to musculoskeletal failure.
ObjectiveTo apply engineering and design principles to orthopaedic biomechanics, to quantitatively assess the musculoskeletal system and model it, and to review rigid-body dynamics in an interesting context.
ContentEngineering principles are very important in the development and application of quantitative approaches in biology and medicine. This course includes a general introduction to structure and function of the musculoskeletal system: anatomy and physiology of musculoskeletal tissues and joints; biomechanical methods to assess and quantify tissues and large joint systems. These methods will also be applied to musculoskeletal failure, joint replacement and reconstruction; implants; biomaterials and tissue engineering.
Lecture notesStored on ILIAS.
LiteratureOrthopaedic Biomechanics:
Mechanics and Design in Musculoskeletal Systems

Authors: Donald L. Bartel, Dwight T. Davy, Tony M. Keaveny
Publisher: Prentice Hall; Copyright: 2007
ISBN-10: 0130089095; ISBN-13: 9780130089090
Prerequisites / NoticeLectures will be given in English.
402-0673-00LPhysics in Medical Research: From Humans to CellsW6 credits2V + 1UB. K. R. Müller
AbstractThe aim of this lecture series is to introduce the role of physics in state-of-the-art medical research and clinical practice. Topics to be covered range from applications of physics in medical implant technology and tissue engineering, through imaging technology, to its role in interventional and non-interventional therapies.
ObjectiveThe lecture series is focused on applying physics in diagnosis, planning, and therapy close to clinical practice and fundamental medical research. Beside a general overview the lectures give a deep insight into selected techniques, which will help the students to apply the knowledge to related techniques.

In particular, the lectures will elucidate the physics behind the X-ray imaging currently used in clinical environment and contemporary high-resolution developments. It is the goal to visualize and quantify microstructures of human tissues and implants as well as their interface.

Ultrasound is not only used for diagnostic purposes but includes therapeutic approaches such as the control of the blood-brain barrier under MR-guidance.

Physicists in medicine are working on modeling and simulation. Based on the vascular structure in cancerous and healthy tissues, the characteristic approaches in computational physics to develop strategies against cancer are presented. In order to deliberately destroy cancerous tissue, heat can be supplied or extracted in different manner: cryotherapy (heat conductivity in anisotropic, viscoelastic environment), radiofrequency treatment (single and multi-probe), laser application, and proton therapy.

Medical implants play an important role to take over well-defined tasks within the human body. Although biocompatibility is here of crucial importance, the term is insufficiently understood. The aim of the lectures is the understanding of biocompatibility performing well-defined experiments in vitro and in vivo. Dealing with different classes of materials (metals, ceramics, polymers) the influence of surface modifications (morphology and surface coatings) are key issues for implant developments.

Mechanical stimuli can drastically influence soft and hard tissue behavior. The students should realize that a physiological window exists, where a positive tissue response is expected and how the related parameter including strain, frequency, and resting periods can be selected and optimized for selected tissues such as bone.

For the treatment of severe incontinence artificial smart muscles have to be developed. The students should have a critical look at promising solutions and the selection procedure as well as realize the time-consuming and complex way to clinical practice.

The course will be completed by a visit of advanced facilities within a leading Swiss hospital.
ContentThis lecture series will cover the following topics:
Introduction: Imaging the human body down to individual cells
Development of artificial muscles
X-ray-based computed tomography in clinics and related medical research
High-resolution micro computed tomography
Phase tomography using hard X-rays in biomedical research
Metal-based implants and scaffolds
Natural and synthetic ceramics for implants and regenerative medicine
Biomedical simulations
Polymers for medical implants
From open surgery to non-invasive interventions - Physical approaches in medical imaging
Dental research
Focused Ultrasound and its clinical use
Applying physics in medicine: Benefitting patients
Lecture notesLink

login and password to be provided during the lecture
Prerequisites / NoticeStudents from other departments are very welcome to join and gain insight into a variety of sophisticated techniques for the benefit of patients.
No special knowledge is required. Nevertheless, gaps in basic physical knowledge will result in additional efforts.
465-0952-00LBiomedical Photonics
Does not take place this semester.
W3 credits2V
AbstractThe lecture introduces the principles of generation, propagation and detection of light and its therapeutic and diagnostic application in medicine.
ObjectiveThe lecture provides knowledge about light sources and light delivery systems, optical biomedical imaging techniques, optical measurement technologies and their specific applications in medicine. Fundamental principles will be accompanied by practical and contemporary examples. Different selected optical systems used in diagnostics and therapy will be discussed.
ContentOptics always was strongly connected to the observation and interpretation of physiological phenomenon. The basic knowledge of optics for example was initially gained by studying the function of the human eye. Nowadays, biomedical optics is an independent research field that is no longer restricted to the observation of physiological processes but studies diagnostic and therapeutic problems in medicine. A basic prerequisite for applying optical techniques in medicine is the understanding of the physical properties of light, the light propagation in and its interaction with tissue. The lecture gives inside into the generation, propagation and detection of light, its propagation in tissue and into selected optical applications in medicine. Various optical imaging techniques (optical coherence tomography or optoacoustics) as well as therapeutic laser applications (refractive surgery, photodynamic therapy or nanosurgery) will be discussed.
Lecture noteswill be provided via Internet (Ilias)
Literature- M. Born, E. Wolf, "Principles of Optics", Pergamon Press
- B.E.A. Saleh, M.C. Teich, "Fundamentals of Photonics", John Wiley and Sons, Inc.
- O. Svelto, "Principles of Lasers", Plenum Press
- J. Eichler, T. Seiler, "Lasertechnik in der Medizin", Springer Verlag
- M.H. Niemz, "Laser-Tissue Interaction", Springer Verlag
- A.J. Welch, M.J.C. van Gemert, "Optical-thermal response of laser-irradiated tissue", Plenum Press
Prerequisites / NoticeLanguage of instruction: English
This is the same course unit (465-0952-00L) with former course title "Medical Optics".
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