SGN-53206 Cell Culturing, Microscopy and Cell Image Analysis, 3 cr

Implementation SGN-53206 2016-01

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 are lectures on techniques for cell image analysis and lectures making use of this knowledge, while taking advantage of a tailored software, which will be used to segment, track, and extract information about the cells previously imaged by the students. In the end, the students will execute a final project, using 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.

Lessons

Assessment scale

Numerical evaluation scale (0-5)

Requirements

Report on experimental works (40% of final grade). Final report on the image analysis project work (60% of final grade). To pass the course, the student is required to: a) Execute the final project and deliver the report on the experimental works. b) Attend at least 80% of all lessons. c) There is no final exam.

Additional information of course implementation

The course is lectured every year. There is no exam. Course webpage: https://www.cs.tut.fi/~sanchesr/SGN-53206/index.htm

Study material