Advanced 3D Anatomical Modeling and Visualization of the Human Cardiorespiratory System using MRI/CT Data

Project Abstract

This study presents a comprehensive framework for high-fidelity 3D anatomical modeling and immersive visualization of the human cardiorespiratory system by integrating multimodal MRI and CT data, with a focus on accurate geometric representation, physiological function, and interactive analysis for clinical and educational applications. We develop a robust data fusion pipeline that leverages thin-slice CT for osseous and vascular structures and MRI sequences for soft tissues, perfusion, and functional dynamics, followed by automated segmentation using deep learning models fine-tuned on clinically diverse datasets. Geometric reconstruction employs surface and volumetric meshing techniques to generate anatomically precise models of the heart, lungs, major vessels, diaphragm, airways, and supporting musculature, preserving topological integrity and enabling realistic deformation under respiratory and hemodynamic conditions. A physics-informed simulation layer integrates cardiovascular hemodynamics with respiratory mechanics, enabling simultaneous pulsatile blood flow and tidal ventilation to explore cardiopulmonary interactions under normal and pathophysiological states such as pulmonary hypertension, COPD, and congenital heart anomalies. The visualization component supports interactive 3D exploration, quantitative metric extraction, and cross-modality registration, providing physicians and educators with synchronized sagittal, coronal, and axial views, as well as time-resolved animations of cardiac cycles and breathing motions. We introduce an annotation-friendly framework that maps clinical landmarks, pathologies, and treatment-relevant regions to a unified atlas, facilitating comparative studies across subjects and interventions. Validation is performed through multiple strands geometric accuracy against ground-truth models and phantoms, functional plausibility assessed by expert cardiologists and pulmonologists, and user-centric evaluation focusing on task performance, cognitive load, and educational efficacy. The system enables scenario-based analyses, such as simulating an occlusion in the coronary arteries or a pneumothorax, and quantifying the resulting hemodynamic and ventilatory perturbations. Performance optimization includes GPU-accelerated rendering, level-of-detail schemes for scalable visualization, and real-time feedback mechanisms to support clinical workflows and interactive teaching sessions. We address challenges in multi-scale registration, tissue differentiation in overlapping intensities, and variability across scanning protocols by introducing a standardized preprocessing pipeline, domain adaptation strategies, and a modular software architecture designed for extensibility. The outcomes demonstrate improved accuracy in organ delineation, enhanced fidelity in motion and deformation modeling, and a versatile platform for preoperative planning, radiology education, and research into cardiopulmonary diseases. The project contributes a reproducible, open-framework methodology that can be adapted to other organ systems, promotes data-driven understanding of cardiopulmonary physiology, and provides a valuable tool for multidisciplinary collaboration among clinicians, biomedical engineers, and educators.

Project Overview

What This Project Is About

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A simple, visual project that creates detailed 3D models of the body's heart and lungs using medical images like MRI and CT scans. It aims to connect what doctors see in scans with interactive 3D visuals to help understand how the heart and breathing system work together.

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The Problem It Addresses

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Medical imaging can be hard to interpret, especially for students or new clinicians. This project fills the gap by turning flat images into accurate 3D models that show how heart and lung structures fit and move together, which can aid learning and clinical planning.

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Objectives of the Project

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1. Convert MRI/CT data into accurate 3D models of the heart and lungs.
2. Provide interactive tools to explore anatomy from different angles and depths.
3. Demonstrate movement and relationships between heartbeats and breathing.
4. Evaluate the models for clarity, accuracy, and educational value with user feedback.

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What You Will Do Step by Step

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1) Gather MRI/CT datasets and learn basic data formats. 2) Segment key structures (chambers, vessels, airways, lungs). 3) Build 3D meshes from segments. 4) Create interactive viewer with simple controls. 5) Animate cardiac and respiratory motion. 6) Validate models against reference anatomy. 7) Collect feedback from peers. 8) Prepare a final demonstration and report.

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Expected Outcome

Working 3D models that accurately depict the heart and lungs, with interactive features and clear explanations. The project should produce a simple tool for education and a foundation for future clinical visualization work.