Image Processing using Python

16 Jan 2024, 13:00 → 19 Jan 2024, 17:00 Europe/Berlin

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Ulf D. Schiller (University of Delaware), Axel Schumacher (KIT), Sikha Ray (KIT), Nicole Merkle (KIT), Thorsten Auth (Forschungszentrum Jülich)

16./17./18./19. January 2024, 1:00 pm to 5:00 pm (Germany) , 7:00 am to 11:00 am (Delaware)

Powered by the University of Delaware, IHRS BioSoft, BIF-IGS, and HIDSS4Health offer a course on "Image Processing with Python" based on the course material provided by Data Carpentry. The course introduces fundamental concepts in image handling and processing. Learners will learn to load images into Python, select, summarise, and modify specific image regions, and identify and extract objects within an image for further analysis.

Course Content

• What scientific questions can we answer with image processing/computer vision?
• What are morphometric problems?
• How are images represented in digital format?
• How can the scikit-image Python computer vision library be used to work with images?
• How can we draw on scikit-image images and use bitwise operations and masks to select certain parts of an image?
• How can we apply a low-pass blurring filter to an image?
• How can we create grayscale and colour histograms to understand an image's distribution of colour values?
• How can we use thresholding to produce a binary image?
• How to extract separate objects from an image and describe these objects quantitatively.
• How can we automatically count bacterial colonies with image analysis?

Course Format

• The course will consist of lectures and hands-on exercises that participants will work on in smaller groups in breakout rooms.

Requirements

• Basic skills in programming with Python, such as those taught on the first two days of our course Python from Zero to Data Science on "First steps" and the last day on "Matplotlib". Please find a detailed list of the required Python skills here.

 

Acknowledgements

Ulf Schiller acknowledges support from the National Science Foundation under Grant No. DMR-1944942. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Please find a schedule for the workshop below. Note that the timings  are for guidance and may change to meet the needs of the course participants.

Places will be confirmed starting early January and the course may be fully booked before the registration deadline on 11 January 2024. In case of overbooking, fellows (members) of the IHRS BioSoft, BIF-IGS, HIDSS4Health, and University of Delaware will be prioritised.

The course is overbooked and there are no promising places on a waiting list available any more; unfortunately, the registration already had to be closed on 10 January 2024 .

Tuesday 16 January

13:00 → 14:45 Lecture and Exercises: Introduction to this course, to images, and scikit-image

13:05 Introduction

General introduction to this course. Scientific questions and morphometric problems dealt with in Image Processing.

13:30 Image Basics

Storing and acting on an image digitally.

14:15 Now you!

Work on and discuss the six tasks on "Image Basics" in breakout rooms.

14:45 → 15:15 Break

15:15 → 17:00 Lecture and Exercises: Working with scikit-image I

15:15 Working with scikit-image

An introduction to scikit-image, a collection of algorithms for image processing.

15:45 Now you!

Work on and discuss the three tasks on "Working with scikit-image" in breakout rooms.

16:30 Drawing and Bitwise Operations

Basic toolkit of scikit-image operators to perform simple analyses of images based on changes in colour or shape.

Wednesday 17 January

13:00 → 14:45 Lecture and Exercises: Working with scikit-image II

13:00 Looking back

Recapitulating yesterday's course content and discussing questions that may have appeared meanwhile.

13:15 Now you!

Work on and discuss the five tasks on "Drawing and Bitwise Operations" in breakout rooms.

14:45 → 15:15 Break

15:15 → 17:00 Lecture and Exercises: Blurring images and creating histograms

15:15 Blurring Images

Blurring as a filter to modify images.

15:45 Creating histograms

Understanding the distribution of colour values in an image.

16:00 Now you!

Work on and discuss the four tasks on "Creating Histograms" and "Blurring Images" in breakout rooms.

Thursday 18 January

13:00 → 14:45 Lecture and Exercises: Thresholding

13:00 Looking back

Recapitulating yesterday's course content and discussing questions that may have appeared meanwhile.

13:15 Thresholding

Thresholding is a type of image segmentation, where we change the pixels of an image to make the image easier to analyze. You will learn how to use scikit-image functions to apply thresholding to an image.

13:45 Now you!

Work on and discuss the five tasks on "Thresholding" in breakout rooms (to be continued after the break).

14:45 → 15:15 Break

15:15 → 17:00 Lecture and Exercises: From Thresholding to Connected Component Analysis

15:15 Now you!

Work on and discuss the five tasks on "Thresholding" in breakout rooms (continued).

15:45 Connected Component Analysis

16:30 Now you!

Work on and discuss the seven tasks on "Connected Component Analysis" in breakout rooms (to be continued tomorrow).

Friday 19 January

13:00 → 14:45 Lecture and Exercises: Connected Component Analysis

13:00 Looking back

Recapitulating yesterday's course content and discussing questions that may have appeared meanwhile.

13:15 Now you!

Work on and discuss the seven tasks on "Connected Component Analysis" in breakout rooms (continued).

14:00 Community-developed checklists for publishing images and image analyses

Do's and Don'ts in image processing: https://doi.org/10.1038/s41592-023-01987-9.

14:45 → 15:15 Break

15:15 → 17:00 Lecture and Exercises

15:15 Capstone Challenge

Hands-on "Morphometrics".

16:15 Conclusions

Concluding remarks and open discussion.