Master Bioimage Analysis Tasks with the IKOSA Knowledge Base

5 Apr, 2022 | Blog posts, IKOSA AI

Since user education has always been a priority to us we have recently launched theIKOSA Knowledge Base – an extensive online repository of microscopy resources for an effective bioimage analysis and algorithm training with the IKOSA Platform. In this general introduction blog post, we present to you the most interesting contents and features of the IKOSA knowledge repository.  

Explore the IKOSA Knowledge Base

If you are new to the IKOSA microscopy image management and analysis platform, you are interested in learning more about some advanced bioimage analysis techniques or you are simply looking for some education materials on the topic of microscopy imaging, the IKOSA Knowledge Base is the right place to start. Explore a large body of web resources, articles, step-by-step video tutorials, helpful visuals and digital information materials our team has prepared for you based on extensive user research, user interviews and frequently asked questions. 

Find the answers to your questions related to the uses of the IKOSA Platform software and practical solutions to your research problems. 

Tips and tricks

The large stock of online resources in our Knowledge Base will help you learn how to easily navigate the IKOSA software and get more efficient and confident in your microscopy image analysis tasks.

Expand your research potential with the IKOSA Knowledge Base repository
Expand your research potential with the IKOSA Knowledge Base repository.

Learning to navigate the IKOSA Knowledge Base 

Get started by learning how to effectively navigate the IKOSA Knowledge Base. The IKOSA Knowledge Base is a publicly available collection of microscopy imaging and analysis resources. To view our information repository no sign-up is required. The IKOSA Knowledge Base is easily accessible on your browser from different devices. 

The content in our knowledge repository is grouped around different topic categories. You can easily view and browse those categories from the user-friendly main navigation page.

The IKOSA Knowledge Base supports search functionality to help you quickly access the information you need. From the main page you have the option to apply search filters and easily find certain terms and information of your interest. You can also search articles included in the Knowledge Base by using label filters.

Finding microscopy resources in the IKOSA Knowledge Base
Search filters in the IKOSA Knowledge base. Find the materials you need applying embedded search filter functionalities.

In the glossary available we provide you with a list of commonly used terms in our instructional articles. The listing includes helpful definitions of key terms in microscopy imaging like for example annotationsemantic segmentation algorithm training and false positive predictions .  

Microscopy resources glossary
Browse central microscopy imaging and analysis terminology in our glossary.

The fundamentals of data and analysis preparation in IKOSA  

In the image management section you will find a series of instructional how-to articles on topics like creating new projects, uploading image data, annotating and labeling images and drawing regions-of-interest (ROIs). All these are basic, but fundamental preparatory steps towards effective image processing jobs in IKOSA and conducting them properly will help you get the optimal research results.   

In the process, we introduce you to many useful tools and features available in the IKOSA software. Learn how to utilize the following specials functionalities:

Microscopy resources image annotation tools
Learn how to use the versatile annotation tools in IKOSA.

Microscopy image analysis and algorithm training tasks with IKOSA

In the algorithm training section you will learn how to train and deploy your own microscopy image analysis algorithms.

In the section dedicated to trained algorithm types we provide theoretical background on the central image analysis techniques available in the IKOSA Platform: semantic segmentation, image classification and object detection.

A special article on algorithm training with IKOSA AI is dedicated to the hows and whats of efficient algorithm development for the purpose of analyzing microscopy image data. Learn how to develop bioimage analysis algorithms on your own that are tailored to your research objectives.

Further, we provide you with helpful instructional materials on the deployment of ready-made algorithms in order to be able to start with actual analytical tasks.  

Learn the hows and whats of custom algorithm development with IKOSA AI
Learn the hows and whats of custom algorithm development with IKOSA AI.

Tips and tricks on algorithm training results interpretation 

Last but not least, getting efficient at interpreting your results output is essential to reaching your research objectives. A group of how-to resources in our Knowledge Base covers both basic and advanced result interpretation techniques

A special article on how to interpret training report results provides you with a better understanding of the underlying data behind trained algorithms. 

Further, we offer comprehensive guidelines on how to interpret quantitative and qualitative result outputs in IKOSA.

Microscopy resources results interpretation
Learn the hows and whats of custom algorithm development with IKOSA AI.

Don’t miss any of our new instructional resources and guides on the IKOSA Knowledge Base

​​​​We keep the IKOSA Knowledge Base up-to-date with new instructional materials and feature updates. So, stick around, if you want to stay current about the latest IKOSA news.

In the meantime follow the educational content on digital microscopy imaging and analysis on our blog to stay updated. 

Ask us your questions to learn more about IKOSA

If you still have questions regarding the capabilities and features of the IKOSA software, feel free to contact us!

Our authors:

KML Vision Team Fanny Dobrenova Marketing Specialist

Fanny Dobrenova

Health communications and marketing expert dedicated to delivering the latest topics in life science technology to healthcare professionals.


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