View Proposal

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Proposer

Radu-Casian Mihailescu

Title

AI-Assisted Generation of Educational 3D Congenital Heart Models from Echocardiography and Anatomical Templates

Goal

To design and evaluate an AI-assisted pipeline for producing simplified 3D congenital heart morphology models using echocardiography data and/or diagnosis-conditioned anatomical templates.

Description

Congenital heart disease can be difficult to explain to parents, junior clinicians, bedside nursing teams, and staff outside specialist cardiac services. Current explanations often rely on hand-drawn diagrams, generic online resources, or non-personalised visual material, which may not fully represent the child’s specific anatomy. This project will explore whether AI methods can support the generation of simplified 3D congenital heart models for education and communication. The project will focus on developing a proof-of-concept system that can generate or adapt a 3D heart model based on available echocardiography data, diagnosis labels, and anomaly-specific anatomical templates. The aim is not to produce a diagnostic or surgical planning tool, but rather an educational visualisation system that could support communication with families and training for non-specialist clinical staff. Objectives - Review existing approaches for 3D heart modelling, echocardiography-based reconstruction, and medical visualisation. - Identify suitable open-source or synthetic 3D heart models that can be used as baseline templates. - Develop a prototype pipeline for adapting a normal neonatal/paediatric heart model into selected congenital anomaly templates. - Explore whether 2D or 3D echocardiography data can be used to guide model adaptation, segmentation, or anatomical parameterisation. - Produce interactive 3D visualisations suitable for educational use. - Evaluate the prototype based on visual quality, anatomical plausibility, usability, and potential educational value. This project is in collaboration with clinicians from Al Jalila Children's Hospital in Dubai

Resources

Background

Url

Difficulty Level

Moderate

Ethical Approval

Full

Number Of Students

1

Supervisor

Radu-Casian Mihailescu

Keywords

Degrees

Bachelor of Science in Computer Science
Bachelor of Science in Computer Systems
Bachelor of Science in Information Systems
Master of Engineering in Software Engineering
Master of Design in Games Design and Development
Master of Science in Artificial Intelligence
Master of Science in Business Information Management
Master of Science in Computer Science for Cyber Security
Master of Science in Computer Systems Management
Master of Science in Data Science
Master of Science in Information Technology (Business)
Master of Science in Information Technology (Software Systems)
Master of Science in Network Security
Master of Science in Software Engineering
Bachelor of Science in Computing Science
Bachelor of Science in Computer Science (Cyber Security)
Postgraduate Diploma in Artificial Intelligence
Bachelor of Science in Statistical Data Science
BSc Data Sciences
MSc Applied Cyber Security