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Workshops & Training

Our world is full of data. Thus, understanding and communicating data is more critical than ever. 

Join the Zeeks ScienceMinds learner community to present your data in the best light possible.

  • Training for scientists and non-scientists alike. 

  • Each course will be adapted to your learner community.

  • Online and in-person courses available.

Send an informal enquiry to learn more.

Scientific Image Processing
For Creatives

Learn about the captivating intersection of art and science in microstructure imaging with this hands-on course. Participants will learn about state-of-the-art microscopy, scientific image processing, and how to bring microscopy science art to life. Creatives will get an insight into how data are generated, perceived by the human brain, and how get insights into the complete workflow how data is transformed from science into science art.

Audience: This course is targeted at people working in creative fields such as architects, artists, photographers, animators, and graphic designers. Everyone interested is welcome!

(1) Science Art: Understand the synergy between art and science in microstructure imaging.
(2) Basic Image Processing: Gain proficiency in Fiji/ImageJ tools for basic image processing. Explore segmentation and other techniques useful for artistic manipulation.

(3) Bring Science Art to Life: Delve into material selection, emphasizing quality and impact,
(4) Practice: Apply acquired skills in individual projects with provided microstructure images.

Biomedical Image Analysis
Beginner

In this introductory image analysis course, we will use the open-source image analysis Fiji to examine, enhance, segment, and quantify provided 3D data. After a one hour lecture, a 3-hour hands on tutorial will examine 3D+ data to provide hands-on practical examples to highlight image analysis workflows, and discuss image analysis in its wider implications.

Audience: This course is targeted at anyone working with microscopy and/or visual data. This course is the ideal choice if you are just getting started with your image analysis journey.

(1) Understanding Data: Understand how 3D data are constructed and what image properties are important in optical fluorescence microscopy.

(2) Image Analysis: Examine and visualize 3D images, understand image properties, and the usefulness of LUTs. Common image analysis steps such as data understanding, image enhancement, segmentation, and quantification.

(3) Hands-on: Using hands-on exercises will provide the attendees with a broader understanding of quantitative image analysis. Attendees will be provided with workbooks as well as real-life data.

(4) Long-term: The tutorial is designed to be interactive with attendees assessing the learned principles.

Biomedical Image Analysis
Intermediate

Participants will use the open-source software Fiji to enhance, segment, and quantify provided 3D data. This includes steps such as optimizing segmentation, skeletonization methods, 3D volumetric analysis. The course includes a one-hour lecture followed by a three-hour hands-on tutorial with practical examples to illustrate advanced workflows and discuss broader implications.

Audience: For this course, participants are expected to have an understanding about multi-dimensional microscopy data and basic Fiji proficiency. If you are unsure, we can also offer a bundle with the beginner course.

(1) Advanced Data Understanding: Delve deeper into 3D data analysis with a focus on optical fluorescence microscopy, emphasizing complex data interpretation and problem-solving. 

(2) Comprehensive Image Analysis: Explore advanced image analysis techniques, including sophisticated data understanding, enhancement, segmentation, and quantification methods. This includes steps such as optimizing segmentation, skeletonization methods, 3D volumetric analysis.

(3) Practical Application: Engage in intensive hands-on exercises designed to deepen your understanding and proficiency in quantitative image analysis.

(4) Reflective Learning: After each tutorial step, participants will have time to reflect on their learning to appreciate the broader implications and applications of the techniques covered. In addition, we will pay attention to how the learned can be used in practice by the attendees by their own data. 

Biomedical Image Analysis
Advanced

In this advanced image analysis course, participants will use the open-source software Fiji and Python to enhance, segment, and quantify provided 3D data. We will use heavily look into code, automation, and how to compare and improve image analysis results. The course includes a one-hour lecture followed by a three-hour hands-on tutorial with practical examples to illustrate advanced workflows and discuss broader implications.

Audience: This course is for advanced image analysis users and require sufficient prior knowledge of attendees. Ideally, all participants are versed with multi-dimensional image analysis and bring some coding experience with them. This course will also look at specific applications, so if you have data you would like to explore, please reach out to us before the course starts. If unsure, a bundle with the beginner or intermediate course is available.

(1) Advanced Data Understanding: Lets take a deep dive into 3D data analysis and complex data interpretation and problem-solving. This course will require prior knowledge on 3D images construction and general image processing (such as filters and segmentation).

(2) Comprehensive Image Analysis:​ Optimize segmentation, apply skeletonization methods, and conduct 3D volumetric analysis (exploration of different methods and Plugins). We will also cover the automation of multi-dimensional data analysis and Macro scripting. In addition, we will compare Macro scripting in Fiji with Python for automating and enhancing image analysis workflows.

(3) Practical Application: Engage in intensive hands-on exercises designed to deepen your understanding and proficiency in quantitative image analysis. Work with real-world datasets to practice and refine skills. Enhancing and analyzing 3D+ images of live cell processes using both Fiji and Python scripts.

(4) Reflective Learning: Discuss the generalization and application of techniques to various types of microscopy data. Evaluating the scalability and efficiency of different image analysis methods.

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