| _version_ | 1866901341149855744 |
|---|---|
| author | Rubina Begam M Nitishkumar G Nandhagopalan E Sanjiv S K Tamilselvan D |
| author_facet | Rubina Begam M Nitishkumar G Nandhagopalan E Sanjiv S K Tamilselvan D |
| contents | Cranial defects resulting from trauma, tumor resection, congenital disorders, or decompressive craniectomy present significant functional and aesthetic challenges. Traditional implant design relies on manual intraoperative shaping or prefabricated generic implants, leading to poor fitting, prolonged surgical time, and suboptimal outcomes. This study proposes a comprehensive digital workflow for patient-specific cranial implant design using Computed Tomography (CT) imaging and open-source 3D modeling tools. The methodology employs CT DICOM images processed through 3D Slicer for threshold-based segmentation (200-3000 HU), volumetric reconstruction, and surface mesh generation. Missing cranial regions are reconstructed using bilateral symmetry-based mirroring, and Boolean operations extract the precise implant geometry. The implant is refined in Meshmixer for thickness uniformity (2.5mm), edge beveling, and surface quality optimization before STL export. Experimental validation on five test cases with defect areas ranging from 15-85 cm² demonstrated mean alignment errors of 0.74mm (maximum 1.12mm), consistent implant thickness, and 100% watertight mesh topology. The complete workflow achieves processing times of 2.4-4.8 hours per case, representing a 70% reduction compared to commercial services, with zero software licensing costs. Results confirm that open-source CT-based workflows can achieve clinically acceptable geometric accuracy for patient-specific cranial reconstruction, making advanced implant design accessible to resource-limited healthcare settings. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19638842 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | CT Image-Based 3D Modeling And PatientSpecific Cranial Implant Design Rubina Begam M Nitishkumar G Nandhagopalan E Sanjiv S K Tamilselvan D Cranial defects resulting from trauma, tumor resection, congenital disorders, or decompressive craniectomy present significant functional and aesthetic challenges. Traditional implant design relies on manual intraoperative shaping or prefabricated generic implants, leading to poor fitting, prolonged surgical time, and suboptimal outcomes. This study proposes a comprehensive digital workflow for patient-specific cranial implant design using Computed Tomography (CT) imaging and open-source 3D modeling tools. The methodology employs CT DICOM images processed through 3D Slicer for threshold-based segmentation (200-3000 HU), volumetric reconstruction, and surface mesh generation. Missing cranial regions are reconstructed using bilateral symmetry-based mirroring, and Boolean operations extract the precise implant geometry. The implant is refined in Meshmixer for thickness uniformity (2.5mm), edge beveling, and surface quality optimization before STL export. Experimental validation on five test cases with defect areas ranging from 15-85 cm² demonstrated mean alignment errors of 0.74mm (maximum 1.12mm), consistent implant thickness, and 100% watertight mesh topology. The complete workflow achieves processing times of 2.4-4.8 hours per case, representing a 70% reduction compared to commercial services, with zero software licensing costs. Results confirm that open-source CT-based workflows can achieve clinically acceptable geometric accuracy for patient-specific cranial reconstruction, making advanced implant design accessible to resource-limited healthcare settings. |
| title | CT Image-Based 3D Modeling And PatientSpecific Cranial Implant Design |
| url | https://doi.org/10.5281/zenodo.19638842 |