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The shown course models are the two standard courses.
Modular changes and combinations are possible according to your needs
“One of the best workshops in the complete PhD program curriculum”
“This course should be compulsory for all scientists working with images and image analysis”
“With the knowledge from these courses, my analyses will be massively faster”
“This workshop is packed with knowledge and it really shows, whoever attends this course, will have the potential to be a better scientist afterwards. Thank you so much for sharing your experience!”
of over 3000 participants recommend the workshop
Scientific digital imaging is very diverse with a huge range of methods and resulting images. The final goal of all scientists is to publish the data in a renowned journal in their field of research. One essential part in publications is to present data in form of figures. Therefore, a least biased choice of representative images of the experiment is already the first critical step (besides prior proper imaging device adjustment and proper image acquisition techniques). Thereafter, images are often subject to editing. The reason/intention for the image editing should already be questioned. Is it applied to improve visibility of features, to direct the observers view to specific regions, to get rid of “ugly background” or dirt from the sample preparation or to underscore points for or against a hypothesis?
Mostly, image editing (as well as image analysis) is done based on good intentions but influenced by natural bias (e.g. our visual system ) and often a lack of sound knowledge in image processing techniques. Not seldom, this leads to alterations in the image data which very quickly might be considered as misrepresentation of data. The Office of Research Integrity (ORI) figured out that from all cases they opened in 2007-2008 for investigation against potential scientific misconduct 68% included image data manipulation .
Of consideration is the fact that images we take in science ARE precious data and need to be handled as such .
In the last years the awareness in this field increased and the number of journals explicitly stating strict image data related guidelines and enforcing compliance is (too) slowly increasing.
Additionally, several whitepapers with a common tenor of suggested guidelines for image processing of scientific images are available , , , , .
Besides those guidelines the education of young scientists in image processing, analysis, handling of scientific images and publication ethics is essential. BioVoxxel is dedicated to communicate skills in good scientific practice regarding digital images to the scientific community to help preventing unintentional image data alterations (see below).
Furthermore, BioVoxxel offers consulting services regarding the assessment of image manipulation