Open Access

ARTICLE

Solid Model Generation and Shape Analysis of Human Crystalline Lens Using 3D Digitization and Scanning Techniques

José Velázquez, Dolores Ojados, Adrián Semitiel, Francisco Cavas^*

Department of Structures, Construction and Graphical Expression, Technical University of Cartagena, Cartagena, 30202, Spain

* Corresponding Author: Francisco Cavas. Email:

Computer Modeling in Engineering & Sciences 2025, 145(2), 1821-1837. https://doi.org/10.32604/cmes.2025.071131

Received 01 August 2025; Accepted 26 September 2025; Issue published 26 November 2025

Abstract

This research establishes a methodological framework for generating geometrically accurate 3D representations of human crystalline lenses through scanning technologies and digital reconstruction. Multiple scanning systems were evaluated to identify optimal approaches for point cloud processing and subsequent development of parameterized solid models, facilitating comprehensive morpho-geometric characterization. Experimental work was performed at the 3D Scanning Laboratory of SEDIC (Industrial Design and Scientific Calculation Service) at the Technical University of Cartagena, employing five distinct scanner types based on structured light, laser, and infrared technologies. Test specimens—including preliminary calibration using a lentil and biological analysis of a human crystalline lens—were digitized under rigorously controlled environmental conditions. Acquired point clouds underwent processing in Rhinoceros software to produce digital surface meshes, which were subsequently converted into solid CAD models via SolidWorks. Model fidelity and biomedical relevance were assessed through quantification of geometric and physical properties. Scanner performance varied significantly in reconstruction precision and resolution, with structured blue light systems (e.g., Artec SPIDER) exhibiting superior capability for capturing lens surface topography compared to infrared or white light alternatives. Resultant models enabled accurate dimensional analysis of clinically relevant parameters including volumetric and surface area measurements. Technology-specific advantages and constraints were rigorously cataloged relative to sample attributes. Findings indicate that structured blue light scanning provides the most effective foundation for crystalline lens digitization and modeling. The presented methodological approach not only ensures high-fidelity solid model generation but also demonstrates translational potential in medical domains, from custom intraocular lens design to refinement of ophthalmic therapeutic interventions.

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