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Updated: May 22, 2026
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Three-Dimensional Reconstruction for the Whole Lung with Early Multiple Pulmonary Nodules
Published on: October 13, 2023
HSI-Based Vector Graphics Algorithm for Enhanced Detection and 3D Visualization of Pulmonary Lesions on CT
Alejandro Hernández-Solís1, Fernando Rogelio Cerezo-Rodríguez1, José Adolfo Rodríguez-Marino1
1Pulmonology and Thoracic Surgery Service, General Hospital of México "Dr. Eduardo Liceaga", Mexico City, Mexico.
Current Medical Imaging
|May 21, 2026
Summary
A new algorithm uses vector graphics and color transformation for fast, low-cost 3D CT reconstructions of thoracic lesions. This method offers high precision for visualizing intrathoracic tumors, improving surgical planning.
Area of Science:
- Medical Imaging
- Computer Graphics
- Radiology
Background:
- Multidetector computed tomography (MDCT) provides high-resolution thoracic imaging.
- Conventional 3D reconstruction methods are costly, time-consuming, and require expertise.
- There is a need for efficient and accessible 3D visualization tools in thoracic imaging.
Purpose of the Study:
- Introduce a novel algorithm (HGM) for low-cost, high-precision 3D reconstruction of intrathoracic lesions.
- To provide an alternative to conventional, computationally expensive 3D CT reconstruction techniques.
- To enable accurate visualization and classification of thoracic abnormalities.
Main Methods:
- The HGM algorithm utilizes vector graphics and RGB-to-HSI color-space transformation.
- Chest CT DICOM datasets were processed with scripted segmentation for organ and lesion isolation.
- Reconstructions were rendered into an interactive format compatible with Adobe Animate®.
Main Results:
- Pilot testing demonstrated accurate 3D reconstruction of an intrapulmonary teratoma for preoperative planning.
- The HGM algorithm achieved a mean processing time of 15 minutes per dataset.
- The method requires modest computational resources and minimal training, making it cost-effective.
Conclusions:
- The HGM algorithm enables rapid anatomical segmentation and dynamic 3D visualization of intrathoracic lesions.
- This approach offers a low-cost, high-precision alternative for 3D CT reconstruction.
- Future research will validate the algorithm for various oncologic and planning applications.
