Course Catalog 2006-2007

SGN-3606 LIGHT MICROSCOPY IN FOUR DIMENSIONS, 3 cr
Light Microscopy in Four Dimensions

Courses persons responsible
Ulla Ruotsalainen

Lecturers
Prof. Pekka Hänninen

Objectives
The aim of the course is to introduce the basic properties of light microscopy with 3D and dynamic options together with the most relevant 3D image processing techniques. This course in intended for students and researchers with some basic knowledge of microscopy and image processing.

Content
Content Core content Complementary knowledge Specialist knowledge
1. Physics of light microscopes
concept of resolution and contrast
different imaging modes
limits of operation
 		 Application areas
fixed sample imaging
live sample imaging
video-microscopy 		   
2. Confocal microscopy from principles to practice:
Principles of confocal optics
theoretical and practical considerations
Practical confocal microscopy
 		 Techniques behind the curtain - preparing the biological samples for imaging.
Specific labelling of biological targets
Fluorescence resonance energy transfer
Application examples 		   
3. Special techniques utilising confocal optics
Fluorescence correlation spectroscopy
Single molecule detection
Two-photon excitation of fluorescence
Resolution enhancement
4Pi confocal microscopy
STED-microscopy 		 On fluorescent labeling.    
4. Automatic analysis of 3-D images
filtering in 3 dimensions (gaussian, anisotropic diffusion)
image segmentation by thresholding
imaging artefacts
motivation for spatial information modeling 		      
5. Spatial prior information in 3-D image segmentation
Markov random fields
deformable models
level sets and gradient flows 		      

Requirements for completing the course
Exam and written review of one of the topics of the course.

Evaluation criteria for the course

  • To pass the course the student has to pass the exam based on the lectures and make a short written review of the given literature material related to the topics of the course.

  • Used assessment scale is passed / failed

    • Prerequisites
    Code Course Credits M/R
    SGN-1107 SGN-1107 Introductory Signal Processing 4 Recommendable
    SGN-1200 SGN-1200 Signal Processing Methods 4 Recommendable
    SGN-1250 SGN-1250 Signal Processing Applications 4 Recommendable
    SGN-3010 SGN-3010 Digital Image Processing I 5 Recommendable
    SGN-3016 SGN-3016 Digital Image Processing I 5 Recommendable

    Prequisite relations (Sign up to TUT Intranet required)

    Remarks

    Additional lectures are given by Prof. Pekka Hänninen, Laboratory of Biophysics, University of Turku and Juhani Soini, Ph. D., ArcDia Ltd.

  • The course is suitable for postgraduate studies.

    • Scaling
    Methods of instructionHours
    Lectures 32
    Assignments 30

    Other scaledHours
    Preparation for exam 20
    Exam/midterm exam 3
    Total sum 85

    Course homepage

    Last modified 29.06.2006
    Modified byKirsi Järnström