Cellular and Molecular Biology

Image Analysis Laboratory

Image Analysis Laboratory

Academic year 2022/2023

Sommario del corso

• Course objectives
• Results of learning outcomes
• Course delivery
• Learning assessment methods
• Support activities
• Program
• Suggested textbooks and readings
• Teaching tools

Course objectives

This teaching contributes to develop a correct approach to the image analysis and quantification.

It also enables students to deepen their knowledge and abilities in the use of the computer, in the manipulation of the images and in the extraction of quantitative data.

Results of learning outcomes

- Ability to use image analysis software, image manipulation programs, and image quantification.
- Understanding the characteristics of the digital image, the principles of morphometry and statistical interpretation.

Course delivery

A series of theoretical lessons, followed by practical work in the laboratory. Home work to be discussed in the following lesson.

This course will thus include as many hours of traditional lessons as is possible for each student. Detailed information will be provided by each teacher based on the type of activity.

All lessons will be delivered in presence. Alternative online teaching (by streaming) may be introduced according to the University recommendations related to the status of the COVID-19 pandemic.

Learning assessment methods

The learning assessment is determined on the basis of the results of a series of laboratory and homeworks, a practical examination on the skills acquired during the laboratory and a final PowerPoint presentation of a plug-in of the Image J program that was not discussed during the laboratory.

Exams will take place exclusively in presence with the only exception of students who self-declare, in relation to Covid-19, personal fragility or positivity.

Remote examinations may be introduced according to the University recommendations related to the status of the COVID-19 pandemic. 

Support activities

Weekly homework sets will be assigned, and their solution will be posted and (if time allows) discussed in class.

Program

Microscopy and Digital Imaging theory
Imaging techniques: light and electron microscopy, sample preparation
Image processing, artifacts and correction filters
Introduction to ImageJ, iLastik and Blender
3D reconstructions and morphometric analysis with ImageJ and Blender
Statistical Analysis

There is no specific textbook for this course. For basic and general reference, see The Image Processing Handbook, 6th edition by J.C. Russ

https://www.amazon.com/Image-Processing-Handbook-Sixth/dp/1439840458

NeuroMorph: A Toolset for the Morphometric Analysis and Visualization of 3D Models Derived from Electron Microscopy Image Stacks
https://link.springer.com/article/10.1007/s12021-014-9242-5

Class schedule

• Teaching materials
• Exams and finals
• Go to Moodle
• Visit the forums