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Zellbildanalyse [CIA]

Summary
The seminar will cover different kinds of image processing and pattern recognition methods that are used for automatic cell image analysis, e.g. image enhancement, segmentation algorithms and classification methods.

Dates & Rooms:
Thursday, 10:00 - 12:00; Room: 09.150


Lecturer

News

07.11.11

The schedule for the seminar an be found here.

 

26.10.11

  • On October 27, the final number of participants is determined, and the topics assigned. In the following days we will detail the topic description and gather the introductory material, which will be uploaded on our website.

 

18.10.11

  • The first meeting will take place thursday, October 20, 10:15 a.m. in seminar room 09.150.
    Points of discussion:
  • Participants
  • Time
  • Location
  • Topics
  • Tasks
Material

Seminar material:

Restricted access, as we cannot put it up without password restriction!

The images and the schedule will follow next week.

 

Superresolution.zip

Superresolution project description

Morphology+ACC.zip

Morphology + ACC project description

 

Presentation of topics:

Initiates file downloadZellbildanalyse.pdf

 

In case of question concerning the topics you can write an email, (Opens window for sending emailsimone.gaffling(at)informatik.uni-erlangen.de), or come by after arranging a meeting beforehand.

Background
Phasenkontrastaufnahme ((c) BVT)

The analysis of cells and their development and behavior under different conditions is of major importance in biotechnology. However, the necessity for human observation is a major drawback. Cell cultures are negatively influenced when they are moved around, and manual counting of individual cells is tedious and error-prone.

 

Automatic methods to extract the necessary information could be of immense benefit. The low contrast and high number of shape types that occur in cell imaging, plus the artifacts due to microscopic visualization is a major challenge though.

 

The seminar will cover different kinds of image processing and pattern recognition methods that are used for automatic cell image analysis.

Content

Topics might include, but are not limited to (students are welcome to suggest own topics):

  • Different microscopes and images generated with them
  • Basic image processing techniques for cell image enhancement
  • Autofocus
  • Pixel-/Region-/Model-based segmentation techniques for cell segmentation
  • Clustering and classification methods
  • ...   

The individual projects mostly comprise a presentation of the theoretical background, plus a programming assignment.

Organisatorisches

Prerequisites:

Programming skills (Matlab, C++),  previous or simultaneous attendance of lectures on Medical Image Processing, Pattern Recognition and/or Pattern Analysis  is of advantage.

Suitable for: Inf, IuK, EEI, CE

Credits: 5 ECTS

Important dates: The first meeting will take place at the beginning of the semester, check back for details!