Tech-Method Course:
Image Analysis II
Date
27-28-29 May 2026
Organizer
Emanuele Martini (IFOM) & Chiara Soriani (IEO)
Location
IEO Campus, Via Adamello 16 - Milan
About the Course
The aim of this course is to help students acquire new skills in the analysis of microscopy images using advanced image analysis tools, through both theoretical lessons and practical hands-on lessons. Students will use state-of-the-art software tools including Fiji programming, Python, and quPath, gaining both computational and analytical skills directly applicable to their research.
Lessons Location: TBD
Image Analysis using Python & Jython
Emanuele Martini, Fabrizio Orsenigo (tutor), Serena Magni (tutor)
9:00 – 12:30
Introduction to Python/Jython programming languages
– From ImageJ macro language to Jython programming language in Fiji
– Python basics: syntax, statements, expressions, list, loops, conditional statements, functions
– From Python to Jython: object oriented programming
– Jython main APIs and Classes for Fiji
– Python vs Jython: Pros and cons
Hands-on: practice on a nuclei segmentation macro and comparison with Jython language
– Implementation of nuclei segmentation
– Focus on Regions Of Interest Manager
– Creation of customized Results table
12:30 – 14:00
Lunch Break
14:00 – 17:00
More complex image analysis and Analysis of Multiple Images
Hands-on: nuclei segmentation with spots count and intensity measurement
– Bio-formats handling
– User interaction
– Multiple channel handling
– Parent-children objects handling
– Multiple Results Table management
– Multiple images analysis
Lessons Location: TBD
Machine Learning and Deep learning in image analysis: semantic segmentation, instance segmentation and image restoration
HT
9:00 – 12:30
Introduction to machine learning and deep learning in image analysis
– Theoretical introduction about machine learning and deep learning
– Machine learning as tool for semantic segmentation/pixel classification
– Deep Learning as tool for image restoration and instance segmentation
Hands-on: Semantic segmentation/pixel classification with Labkit
12:30 – 14:00
Lunch Break
14:00 – 17:00
Image restoration and instance segmentation using Deep Learning in Python
– Introduction to Jupyter (Python) notebooks and their use in cloud with ZeroCostDL4Mic
– Deep Learning algorithms for image restoration and instance segmentation
Hands-on: Image restoration and nuclear segmentation with Deep Learning algorithms
– Image restoration using Noise2Void algorithm; model training and application using Jupiter notebooks in ZeroCostDL4Mic
– Nuclear segmentation using 2D and 3D Stardist using Jupyter notebooks in ZeroCostDL4Mic
Lessons Location: TBD
Application: Deep Learning tools for cell segmentation
Chiara Soriani/IEO TBD
9:00 – 12:30
Segmentation in tissues using Stardist with QuPath software
– Introduction to QuPath for tissue sections analysis
– Cell segmentation in tissues
Hands-on: Cell segmentation in tissues using Stardist and cell-type classification in different populations
12:30 – 14:00
Lunch Break
14:00 – 17:00
Cell segmentation using Cellpose software in Python
– Introduction to conda environments and their utility for using local Jupyter (Python) notebooks
– CellPose Deep Learning software for cell and nuclear segmentation
Hands-on: Segmentation of cells and nuclei using CellPose and evaluation of cytoplasmic signal using local Jupyter notebooks
Wrap up and discussion