FutureLearn

Statistical Shape Modelling: Computing the Human Anatomy (FutureLearn)

Offered by University of Basel,

Learn the technology of modelling, as used in computational face recognition or in surgeries, with this free online course. Statistical shape models are one of the most important technologies in computer vision and medical image analysis. With this technology, the computer learns the characteristic shape variations of an object or organ. The model resulting from this analysis may then be used in implant design, image analysis, surgery planning and many other fields.

Class Deals by MOOC List - Click here and see FutureLearn's Active Discounts, Deals, and Promo Codes.

In this free online course, you will get insights from mathematics, statistics and machine learning, in order to address practical problems, as well as a theoretical and practical introduction to the open source software Scalismo.

Syllabus

Week 1: Basic concepts of shape modelling and the Scalismo software
Week 2: Building shape models: fundamental concepts in theory and practice
Week 3: Probabilistic aspects of shape models
Week 4: Modelling with Gaussian Processes
Week 5: Reconstructing missing parts
Week 6: Fitting models to data
Week 7: Model-based image analysis
Week 8: Conclusion and outlook

What will you achieve?
By the end of the course, you'll be able to...

Model the normal shape variations of anatomical shapes using Gaussian processes
Explore the mathematical concept of Gaussian processes visually on 3D shapes
Apply the theoretical concepts of shape modelling to clinically relevant problems in shape and image analysis
Develop programs for building and fitting statistical shape models to images using the open source software Scalismo

Who is the course for?
This course is intended for students and professionals with a Bachelor in computer science, medical imaging professionals and biological anthropologists, who are interested in top-notch research, scientific insights and a useful application. Please note that tutoring takes place between March 1, 2021 and May 2 2021
Although you can watch the videos, read the articles, and complete the tests and quizzes on mobile devices such as smartphones or tablets, you will have to install the free software Scalismo on your own workstation in order to use it – there is no online version available.
In order to be able to do this, your computer should meet the following minimum system requirements: Windows (32bit/64bit), Mac OS X or Linux (64bit), 4GB of RAM, 500MB of free HD space. There are no special requirements for the graphic adapter.

Go to Class

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Coursera

University of Michigan

Introduction to 3D Modeling (Coursera)

CS: Design & Product

On this four-week practical course from the University of Michigan, you’ll not only learn how to use the Rhino software to create your 3D models, but you’ll also gain basic design skills to help bring your imagination to life. This course will guide you through 3D modeling within Rhino, so you’ll cover the fundamentals of the software as well as 3D modeling in general. You’ll first look at how to navigate the user interface and the different tools that you’ll be using to create models throughout this course. You’ll familiarize yourself with the 3D space and 3D objects before jumping straight in to create your own objects and building blocks.

Sep 7th 2026

4 Weeks

3D 2D Modeling

Coursera

Universidad de los Andes

Modelaje y Análisis con información georreferenciada (Coursera)

Statistics & Data Analysis Data Science

El curso modelaje y análisis con información georreferenciada busca que comprendas la diversidad y el potencial de los datos geográficos. En el curso podrás utilizarlos en ejemplos básicos para modelar, procesar y analizar problemas donde la ubicación juega un rol importante. Todo esto con el fin de encontrar soluciones que te permiten un primer acercamiento práctico para el procesamiento de este tipo de datos no tradicionales.

Aug 31st 2026

4 Weeks

Modeling Geographic Information Geospatial Analysis

FutureLearn

Raspberry Pi Foundation

Prepare to Run a Code Club (FutureLearn)

Teacher Professional Development Computer Science

Build your confidence and get practical advice on launching and running a Code Club for young people. Code Club is a global network of volunteers and educators who run free coding clubs for 9- to 13-year-olds. This short course will give you the confidence and skills to run a Code Club for young people and inspire the next generation to get excited about computing and digital making.

Feb 1st 2021

3 Weeks

Learning Computing Teaching

FutureLearn

Raspberry Pi Foundation,National Centre for Computing Education

Programming Pedagogy in Secondary Schools: Inspiring Computing Teaching (FutureLearn)

CS: Programming

Examine a range of pedagogical approaches suitable for teaching computing in Key Stage 3 (Grade 6–8 in the USA). Transform your teaching by developing your pedagogical approach. In the first two weeks of this course, you’ll be introduced to a range of pedagogical approaches suitable for Key Stage 3. You’ll look at a range of pedagogies aimed at developing your students’ computational thinking skills, from unplugged approaches to PRIMM, and more. You’ll also investigate worked examples and targeted tasks such as Parson’s Problems.

Mar 6th 2023

3 Weeks

Programming Education Computing

Coursera

University of Melbourne,The Chinese University of Hong Kong

Basic Modeling for Discrete Optimization (Coursera)

CS: Software Engineering

Optimization is a common form of decision making, and is ubiquitous in our society. Its applications range from solving Sudoku puzzles to arranging seating in a wedding banquet. The same technology can schedule planes and their crews, coordinate the production of steel, and organize the transportation of iron ore from the mines to the ports. Good decisions in manpower and material resources management also allow corporations to improve profit by millions of dollars.

Sep 14th 2026

4 Weeks

Programming Software Discrete Optimization

Coursera

Politecnico di Milano

FPGA computing systems: Background knowledge and introductory materials (Coursera)

CS: Design & Product

This course is for anyone passionate in learning how a hardware component can be adapted at runtime to better respond to users/environment needs. This adaptation can be provided by the designers, or it can be an embedded characteristic of the system itself. These runtime adaptable systems will be implemented by using FPGA technologies.

Sep 7th 2026

4 Weeks

Computing Hardware FPGA

Coursera

Rice University

Algorithmic Thinking (Part 1) (Coursera)

CS: Theory

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems.

Sep 7th 2026

4 Weeks

Python Computing Algorithms

Coursera

EDUCBA

Foundation to Multi-Cloud (Coursera)

CS: Information & Technology

The "Foundation to Multi-Cloud" course is designed to provide a comprehensive understanding of multi-cloud computing principles, benefits, and challenges. It equips you with the knowledge and skills required to effectively manage and utilize multiple cloud platforms simultaneously. This course introduces the concept of multi-cloud, elucidates its advantages and complexities, and delves into various strategies and technologies for implementing and managing multi-cloud environments.

Sep 7th 2026

3 Weeks

Security Computing Cloud Computing

Coursera

Johns Hopkins University

Computing for Cancer Informatics (Coursera)

Health & Society

One of the key cancer informatics challenges is dealing with and managing the explosion of large data from multiple sources that are often too large to work with on typical personal computers. This course is designed to help researchers and investigators to understand the basics of computing and to familiarize them with various computing options to ultimately help guide their decisions on the topic.

Sep 7th 2026

4 Weeks

Computing Cloud Computing Bioinformatics

Coursera

Rice University

An Introduction to Interactive Programming in Python (Part 2) (Coursera)

CS: Software Engineering CS: Programming

This two-part course is designed to help students with very little or no computing background learn the basics of building simple interactive applications. Our language of choice, Python, is an easy-to learn, high-level computer language that is used in many of the computational courses offered on Coursera. To make learning Python easy, we have developed a new browser-based programming environment that makes developing interactive applications in Python simple.

Sep 7th 2026

4 Weeks

Game Programming Python

Coursera

DeepLearning.AI

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (Coursera)

CS: Software Engineering Computer Science

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.

Sep 14th 2026

4 Weeks

Artificial Intelligence Machine Learning Neural Networks

Coursera

Rice University

Principles of Computing (Part 1) (Coursera)

CS: Software Engineering

This two-part course builds upon the programming skills that you learned in our Introduction to Interactive Programming in Python course. We will augment those skills with both important programming practices and critical mathematical problem solving skills. These skills underlie larger scale computational problem solving and programming.

Sep 7th 2026

5-12 Weeks

Programming Python Probability