Image Dataset Quality Control, Data Exploration and Pixel Patrol

This two-part online workshop introduces best practices for image dataset quality control and exploration. You’ll learn how to identify dataset issues, visualize distributions and metadata, and prepare images for downstream analysis, using PixelPatrol as a practical support tool. After applying PixelPatrol to your own datasets, you’ll reconvene to discuss questions, review results, and sharpen your insights—helping you turn raw image collections into high-quality, analyzable data.

Registration will open on August 13.

Instructor

Ella Bahry, Engineering and Support Unit at MDC

Learning Goals

Session 1 – Concepts and Tools

• Understand key principles of image dataset quality control and why early validation matters.
• Learn how to identify common dataset issues (outliers, inconsistent metadata, acquisition differences).
• Explore dataset statistics and visual summaries for structure, balance, and potential biases.
• Get hands-on experience using PixelPatrol for dataset-wide visualization, metadata inspection, and report generation.

Session 2 – Application and Reflection

• Apply PixelPatrol to your own datasets and interpret its outputs.
• Troubleshoot real-world dataset issues found by PixelPatrol.
• Discuss results and strategies for improving data quality.
• Develop a workflow for integrating dataset validation into your research pipeline.

Prerequisites

To participate in this course, it is best to have familiarity with digital images and image processing.

Target Group

This course mainly targets researchers working with image datasets in fields such as microscopy, biomedical imaging, earth and material science.

Course Days & Times

Sep 10, 2026, 10:00 – 11:30 AM CEST

Sep 17, 2026, 10:00 – 11:30 AM CEST

Attendance & Certificates

The course content is coordinated, so we strongly recommend that you do not miss any part of the course. To receive a certificate we expect full time and active participation.

Registration & Cancellation

This course is open to individuals affiliated with Helmholtz or a HIDA Partner only.

Your registration for this course is binding. If you need to leave/miss the course for a period of time, please let us know in advance via hida-courses@helmholtz.de.

If you have to cancel the course for any reason, please do so as soon as possible to allow time for others to take your seat. To cancel, please withdraw your registration on the course site or write an email to hida-courses@helmholtz.de.

Additional Information

There is no waiting list for this course! If someone withdraws from a course, their place is automatically reopened. We therefore advise you to keep an eye on the registration in case the course is fully booked and you would like to attend. Also, this course will be offered again in the future – you can check our HIDA course catalog for updates.

This course is free of charge, and is part of the data science course portfolio offered by the platforms of the Helmholtz Information and Data Science Framework.