In this interview, NewsMed speaks with Georgia Golfis, European Imaris Team Representative, about the launch of Imaris 11 and how its new workflow-driven approach is transforming image analysis through automation, reproducibility, and intelligent batch processing.
Can you please introduce yourself and your role at Imaris?
My name is Georgia Golfis, and I am part of the European Imaris team.
I work closely with users to support their image analysis needs and help them get the most out of the software. Normally, new Imaris versions are presented by our Product Manager, Anna Paszulewicz, who oversees development from conception to launch. On this occasion, I had the pleasure of presenting Imaris 11 on her behalf.
What is Imaris 11, and what is the main focus of this release?
Imaris 11 is built around the central goal of accelerating and simplifying image analysis while ensuring reproducibility.
The core innovation in this version is the introduction of workflows. These workflows are intuitive, step-by-step protocols that automatically record every action performed during image analysis. The objective is to eliminate repetitive manual documentation while improving consistency and reproducibility across experiments.
Why was workflow automation prioritized in Imaris 11 development?
The decision was driven by user feedback. Image analysis is often repetitive and time-consuming, and many users struggle to document complex protocols or share them with collaborators. Reproducibility is critical in scientific research, yet manually recording parameters, filtering steps, and object creation settings is both inefficient and error-prone.
By listening to our users’ daily challenges, we designed workflows to automatically capture every step in the analysis process. This ensures that protocols can be reliably reproduced and easily shared.
How do workflows improve reproducibility in image analysis?
Workflows automatically document everything that happens during analysis. This includes object creation details, filtering decisions, masking, channel editing, statistical exports, and even snapshots.
Instead of writing detailed notes, users now generate a live workflow file that records the entire protocol. When someone imports that workflow, they can see exactly what was done, in what order, and with which parameters. This dramatically improves reproducibility and transparency in image analysis.
Can workflows handle both automated and manual analysis steps?
Yes, and that is one of their strengths. If a workflow includes manual steps, such as drawing a region of interest, the batch process pauses and prompts the user for input before continuing.
This hybrid approach allows users to combine automation with necessary expert-driven decisions, without sacrificing efficiency when processing multiple datasets.
How does Imaris 11 simplify batch processing?
Once a workflow is created and validated on a control image, it can be applied to multiple images with just two clicks. The same protocol can be executed across experimental groups, ensuring consistency.
Additionally, workflows can include automatic snapshot generation. After batch processing, users can perform quality control across all images without reopening each file individually. This saves substantial time in large studies.
How does Imaris 11 support side-by-side comparison of experimental groups?
The plotting interface makes it easy to compare datasets. After applying a workflow to multiple images, quantification results can be analyzed side by side.
Users can compare experimental groups with a single click, streamlining the process of identifying biological differences across conditions. This integrated approach enhances both efficiency and analytical clarity.
What changes were introduced to the user interface in Imaris 11?
One of the noticeable updates is the separation of tools into two columns: Visualization and Workflows.
The Visualization column displays objects currently present in the scene and provides access to rendering tools. The Workflow column contains quantification tools and records each analysis step. This clear separation improves usability and helps users track the progression of their image analysis protocol.
Image Credits: Oxford Instruments
Can you give a practical example from the webinar?
In the webinar, we analyzed cancer cells grown in micro-patterned shapes. The experiment involved multiple fluorescence channels, including nuclei, cytoskeleton, protein expression, and lysosomes.
We developed a workflow to detect cells using machine learning and then quantified lysosomes within each cell. The aim was to measure lysosome numbers, sizes, and densities in control and treated samples. Once the workflow was validated, it could be applied automatically to all experimental groups, ensuring consistent analysis.
How does Imaris 11 support learning and onboarding for new users?
For this release, we introduced downloadable self-learning demo images available from the Imaris website. Each dataset includes the raw image, the analyzed version, and the associated workflow file.
Users can open the analyzed data, examine the workflow, and then apply it to the raw dataset. This enables structured self-study and helps new users understand both the workflow concept and the broader image analysis capabilities of Imaris 11.
How does Imaris 11 facilitate collaboration between researchers?
Workflows are lightweight files that can be shared via email. This makes it simple to distribute validated image analysis protocols across labs or institutions.
Researchers can import a workflow, examine every step and parameter, and apply it directly to their own data. This ensures consistency across collaborative studies and reduces ambiguity in methodological reporting.
What are the broader implications of Imaris 11 for scientific research?
Imaris 11 addresses two critical needs in modern science: efficiency and reproducibility. By automating documentation, enabling batch processing, and simplifying protocol sharing, it reduces human error and saves valuable time.
Ultimately, it empowers both experts and non-experts to perform reliable, standardized image analysis, accelerating discovery while maintaining scientific rigor.
About Georgia Golfis 
Georgia Golfis is a member of the European Imaris team, supporting researchers in advanced microscopy image analysis and quantification. With a background in life sciences and extensive experience in imaging technologies, she works closely with scientists across academia and industry to optimize experimental workflows and analytical reproducibility. Georgia's expertise spans fluorescence microscopy, 3D and 4D imaging, and quantitative image analysis. As part of the Imaris team, she contributes to user training, application support, and the introduction of new software capabilities designed to streamline research workflows. She also collaborates with multidisciplinary teams to translate complex imaging data into meaningful biological insights, ensuring that researchers can fully leverage automated and machine learning-driven tools. Through her work, Georgia plays a key role in communicating product innovations such as Imaris 11, helping the scientific community adopt more reproducible and efficient image analysis strategies.
About Oxford Instruments
Oxford Instruments is a leading provider of high-technology tools and systems for research and industry, dedicated to accelerating breakthroughs that create a brighter future for our world. With a global presence, we are committed to innovation and excellence, offering cutting-edge solutions that enable researchers and industry professionals to achieve breakthroughs in their fields. Our advanced technologies deliver numerous benefits through unparalleled precision and reliability, allowing users to obtain accurate and reproducible results. By utilising Oxford Instruments' innovative solutions, research is accelerated, productivity is enhanced, and innovation is achieved in various fields, including materials analysis, life sciences, semiconductors, physics, chemistry, and food sciences. We take pride in being a trusted partner for those aiming to push the boundaries of scientific and industrial advancements, providing the tools and support necessary to realise their visions.
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