MONAI Training

This training covers how to get started with machine learning in the medical field.

Slicer

Objectives

  1. Discover machine learning in the medical field
  2. Discover the tools to develop, visualize and integrate machine learning models in 3D data (MRI, CT)
  3. Practise semantic segmentation and classification with the MONAI framework

Prerequisites

  • Python: basic knowledge
  • Machine learning: basic knowledge would be a plus
  • Image processing: basic knowledge would be a plus

Program

  • Machine learning in the medical field
    • Medical Machine Learning applications
    • Medical AI Adoption challenges
    • State of the art
  • Gettings started with MONAI
    • Introduction to MONAI
    • Feature overview
    • Setting up your environment
  • MONAI Transforms
    • Introduction to the concept of Transforms
    • Preprocessing Transforms
    • Post processing Transforms
  • MONAI Datasets, Caching and Networks
  • End-To-End Workflow with MONAI
    • Semantic segmentation
    • Classification
  • MONAI Label
    • Features
    • Gettings started
    • Customizing MONAI Label
  • MONAI model deployment and integration
    • Development lifecycle
    • Deployment Options
    • MONAI Deploy
    • Federated Learning

This training course will be taught in English. Course notes are also in English.
Participants are asked to bring a laptop computer for this training session.
The instructor will communicate all the specifications required to each participants before the training session.

Kitware SAS is registered as a training center in France

Practical Information

Duration: 1 day
Next training Date: October 9, 2024
Time zone: Paris (CET / GMT+1h)
Schedule: 9am to 5pm
Location: Online
Price: 800€

Company Training

All our training can be offered on site with a custom agenda. Contact us for more information.

A propos du formateur

Roman joined Kitware’s European offices in Lyon as an R&D engineer in April 2022.

Roman has a computer science engineering degree from Telecom ParisTech (Paris), during which he specialized in image processing, computer vision and medical imaging.

Prior to joining Kitware, Roman worked at the IADI laboratory in Nancy, his main areas of focus were on the reconstruction and advanced image processing in breast diffusion MRI and the automatic classification of tumors by texture analysis in MRI and CT Scan.

Thanks to his academic and professional background, Roman mainly works on medical image processing projects.