Zur Seitennavigation oder mit Tastenkombination für den accesskey-Taste und Taste 1 
Zum Seiteninhalt oder mit Tastenkombination für den accesskey und Taste 2 


Name des Moduls [116810] Image Processing in Microscopy Modulcode PAFMO181

Studiengang [128] Physik ECTS Punkte 4 LP

Arbeitsaufwand für Selbststudium 75 Stunden Häufigkeit des Angebotes (Modulturnus) jedes 2. Semester (ab Wintersemester)
Arbeitsaufwand in Präsenzstunden 45 Stunden Dauer des Moduls 1 Semester
Arbeitsaufwand Summe (Workload) 120 Stunden    


Prof. Dr. Rainer Heintzmann

Voraussetzungen für die Vergabe von Leistungspunkten

Written or oral examination (100%).

The selected form of the exam will be announced at the beginning of the semester.


Englisch, Deutsch auf Nachfrage

Voraussetzungen für die Zulassung zum Modul



All the image processing and simulations will be practiced in exercises. The student needs to be familiar with programming at a basic level and with basic concepts of image processing such as filtering and thresholding. The Image Processing lecture by Prof. Denzler in the second term forms a good basis for this course.

Art des Moduls

128 M.Sc. Physik Vertiefung „Optik”: Wahlpflichtmodul

628 M.Sc. Photonics: Wahlpflichtmodul

Zusammensetzung des Moduls / Lehrformen

Vorlesung: 2 SWS

Übung: 1 SWS


We will show different methodologies to extract specific information such as for example the average speed of diffusing particles or the locations and areas of cells from the multidimensional image data. Also fitting quantitative models to extracted data will be treated.Simulation of far-field intensity distribution by using simple Fourier-space based approaches is treated with and without considering the vectorial nature of the oscillating electro-magnetic field.

Lern- und Qualifikationsziele

Current microscopy often acquires a large amount of image data from which the biological or clinical researcher often needs to answer very specific questions.A major topic is the reconstruction of the sample from the acquired, often complex, microscopy data. To solve such inverse problems, a good model of the data acquisition process is required, ranging from assumptions about the sample (e.g. a positive concentration of molecules per voxel), assumptions about the imaging process (e.g. the existence of an incoherent spatially invariant point spread function) to modeling the noise characteristics of the detection process (e.g. read noise and photon noise). The students will be enabled to solve related problems.

PAFMO181 ... Image Processing in Microscopy Modulhandbuch

Impressum | Datenschutzerklärung