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Course Catalog 2014-2015
SGN-53206 Cell Culturing, Microscopy and Cell Image Analysis, 3 cr
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Lessons
| Study type | P1 | P2 | P3 | P4 | Summer | Lecture times and places |
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Description:
Signal Processing is becoming a key specialty in biology related efforts, both in research and in industry. However, signal processing students, in general, currently lack any experience in the experimental techniques and methods they will be required to understand to analyze and interpret the data that arises from them. In this course, students will be introduced to current techniques of cell culturing and imaging. Students will also be provided with knowledge of state-of-the-art algorithms for analyzing cell images. This course will be taught using a hands-on approach. Students will first be provided with one introductory lecture on the biological topics, such as cell culturing and cell imaging using microscopy. The following lesson will be experimental, in which the students will culture their cells. This is followed by a lesson where the cultured cells are imaged under the microscope. Next, there is a lecture on state of the art tools for cell image analysis, such as CellProfiler and ImageJ, which will then be used in the following three lectures to segment, track, and extract information about the cells previously imaged by the students. In the last lecture, as a final project, the student will use signal processing tools to analyze the data they have produced. The aim of the analysis will be chosen by the student from a set of proposed goals or proposed by the student.
Person responsible:
Andre Sanches Ribeiro
Target groups:
Biotekniikka
DI- ja arkkitehtiopiskelijat
International Students
Jatkotutkinto-opiskelijat
Signaalinkäsittely ja tietoliikennetekniikka
Tekniikan kandidaattiopiskelijat
Teknis-luonnontieteellinen
Ympäristö- ja energiatekniikka
Assessment scale:
Numerical evaluation scale (1-5) will be used on the course
Additional information of course implementation:
The course is lectured every year. There is no exam. Course webpage: http://www.cs.tut.fi/~sanchesr/SGN-53206/index.htm