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Related Experiment Video

Updated: Dec 14, 2025

Author Spotlight: Advancing Human Cardiac Anatomy Through Multi-Scale Analysis of Hearts

Author Spotlight: Advancing Human Cardiac Anatomy Through Multi-Scale Analysis of Hearts

Published on: June 28, 2024

Four-dimensional virtual reality cine cardiac models using free open-source software.

Sarv Priya¹, Prashant Nagpal²

¹Department of Radiology, University of Iowa Hospitals & Clinics, 200 Hawkins Drive, Iowa City, IA, 52242, USA. sarv-priya@uiowa.edu.

Pediatric Radiology

|July 19, 2020

Summary

This summary is machine-generated.

This study demonstrates a new method for creating dynamic, four-dimensional (4-D) heart models using accessible software and hardware. These virtual reality models offer real-time visualization for education and surgical planning, overcoming limitations of static 3-D prints.

Keywords:

Augmented reality Children Congenital heart disease Dynamic cine cardiac model Four-dimensional models Heart Three-dimensional printing Virtual reality

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Area of Science:

Medical Imaging
Computational Biology
Virtual Reality

Background:

Static 3-D printed cardiac models lack dynamic visualization capabilities.
Current virtual/augmented reality cardiac models often use expensive software or segment only one cardiac phase.
There is a need for accessible, multiphase cardiac modeling for clinical applications.

Purpose of the Study:

To develop a proof-of-concept for creating four-dimensional (4-D) cine heart models.
To visualize these 4-D models in virtual reality (VR).
To utilize freely available open-source software and inexpensive hardware for the process.

Main Methods:

Developed a method for multiphase cardiac segmentation.
Implemented visualization of 4-D cine models in VR.
Utilized open-source software and affordable hardware.

Main Results:

Successfully created a 4-D cine model of the heart.
Demonstrated VR visualization of the dynamic cardiac model.
The approach uses accessible tools, overcoming cost barriers.

Conclusions:

This study presents a feasible approach for multiphase cardiac segmentation and VR visualization.
The method offers a cost-effective alternative to existing technologies.
Potential applications include patient education, trainee instruction, and surgical planning for complex congenital heart disease.