Login |
 
 

Overview

Credits: SWS : 2, Credits 4

Participants: Min: 1 Max: 12 Expected: 8

Course type : Seminar

Language: english

Materialien

Description

The availability of automated microscopy and fast imaging methods in combination with fluorescent protein labeling produces a huge amount of n-dimensional image data. Manual analysis of this image data is very time-consuming and hardly reproducible. As a result demand for algorithms to quantify biological image data is increasing. In this seminar, students will work on datasets from current or previous bio-imaging data challenges and solve a given image processing task using  open-source software solutions. Students will apply algorithms from the fields of image preprocessing, segmentation, clustering, tracking, classification or further related areas.

A sucessful participation of the seminar includes:

  • 20 to 25 minutes presentation of the results.
  • Documented and reusable solution of the presented approach.
  • 10-15 pages project-report.

Literature

KNIME Image Processing Framework:
tech.knime.org/community/image-processing

FIJI:
fiji.sc

ImgLib2:
github.com/imglib/imglib2
imglib2.net

ImageJ-Ops:
github.com/imagej/imagej-ops

CellProfiler:
cellprofiler.org

Ilastik:
ilastik.org

Important

Registration via StudIS required.

Preliminary discussion of the topics: Fr 04/24/2015, 1:00 - 2:00 pm

Participating in https://lsf.uni-konstanz.de/qisserver/rds?state=verpublish&status=init&vmfile=no&publishid=48049&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung is mandatory