Course Principles and approaches to digital image processing and analysis

The course C290/02 Principles and approaches to digital image processing and analysis is being offered by the Graduate School of Health, Aarhus University, 2023.

Criteria for participation: University degree in medicine, dentistry, nursing, or master’s degree in other fields and/or postgraduate research fellows (PhD students and research-year medical students).

Recommended knowledge for participation: Experience with ImageJ and basic image analysis.

Application: In order to apply for course participation, you must:

1. Sign up for the course here on PhD Course Management
2. Submit an application (max. 250 words in English)

Application must be submitted to course administrator on mail courses.nat.tech.he@au.dk no later than 2 weeks before application deadline.

Aim: The goal of this hands-on course is to survey the fundamentals of how image pixel data can be used to extract biologically meaningful information. Participants will install FIJI and will be given ample opportunity to work on actual images for a truly hands-on learning experience. Opportunities to discuss individual projects will also be available.

Learning outcomes: Participants will gain practical experience with FIJI and basic principles of imaging processing. Learning outcomes include increased skills in image denoising, segmentation, colocalization, and particle tracking.

Workload: The full workload of the course is expected to be 57,5 hours.

Content: The course touches the following elements:

• Fundamentals of Digital Images

The underlying operation of digital photon detectors, how detector parameters affect image quality and accuracy, fundamental concepts of digital images, image correction, file format, colour format, image compression.

• Basic Principles of Image Processing

Linear and non-linear operation, neighbourhood- and non-local denoising approaches, image filters, feature enhancement techniques, edge detection.

• Fourier Transformation

Principles of Fourier transformation and its applications in image processing, apodization filter, frequency space and optics, use of Fourier transformation in microscopy

• Object Segmentation

Approaches to object segmentation: watershed, morphological filters, image threshold, 1st, and 2nd order derivative object-recognition methods

• Machine-learning and Object Segmentation

Underlying principles of machine learning in image processing; Weka trainable object segmentation

• Object-based Colocalization

Introduction to Boolean arguments, image intersection and image union

• Intensity-based Measurement and Analysis

Digital analysis of intensity measurement, pixel-based colocalization (Pearson’s, Manders’, and Spearman’s coefficients), intensity modulated display in ratiometric image analysis

• Tracking Biological Changes and Movement

Kymograph, measurement of structural changes, localization precision, tracking movement, mathematical description and modelling of translocation behaviour

Instructors: Director, Teng-Leong Chew and Bioimage Data Analyst, Rachel Lee, Advanced Imaging Center, Janelia Research Campus, USA

Venue: Aarhus University, Aarhus

Participation in the course is without cost for:

• PhD students, Health Research Year students and Health Research Honours Programme students from Aarhus University
• PhD students enrolled at partner universities of the Nordoc collaboration
• PhD students from other institutions in the open market agreement for PhD courses

Course dates:

• 19 June 2023 10:00 - 11:00
• 20 June 2023 09:00 - 16:00
• 21 June 2023 09:00 - 16:00
• 22 June 2023 09:00 - 16:00