KneeBones3Dify is a Python software tool that supports detailed analysis of knee pathologies and preoperative planning for knee replacement surgery based on patient-specific 3D models. It produces printable 3D bones in a stereolithography file format by automatically segmenting the femur, patella, and tibia from high-resolution Magnetic Resonance (MR) images with nearly isotropic voxel dimensions. Our software avoids time-consuming and subjective manual segmentation by specialists, offering an accurate and efficient alternative employing GPU acceleration. We validated the results by computing objective metrics against the ground truth voxel-wise segmentation produced for a 3D MR image by specialists, who also confirmed the reconstruction accuracy qualitatively. KneeBones3Dify and annotated data are publicly available, enabling broader research and clinical practice use.

KneeBones3Dify: Open-source software for segmentation and 3D reconstruction of knee bones from MRI data / Maddalena Lucia; Romano Diego; Gregoretti Francesco; De Lucia Gianluca; Antonelli Laura; Soscia Ernesto; Pontillo Gabriele; Langella Carla; Fazioli Flavio; Giusti Carla; Varriale Rosario. - In: SOFTWAREX. - ISSN 2352-7110. - ELETTRONICO. - 27:(2024), pp. 101854.0-101854.0. [10.1016/j.softx.2024.101854]

KneeBones3Dify: Open-source software for segmentation and 3D reconstruction of knee bones from MRI data

Romano Diego;Pontillo Gabriele;
2024

Abstract

KneeBones3Dify is a Python software tool that supports detailed analysis of knee pathologies and preoperative planning for knee replacement surgery based on patient-specific 3D models. It produces printable 3D bones in a stereolithography file format by automatically segmenting the femur, patella, and tibia from high-resolution Magnetic Resonance (MR) images with nearly isotropic voxel dimensions. Our software avoids time-consuming and subjective manual segmentation by specialists, offering an accurate and efficient alternative employing GPU acceleration. We validated the results by computing objective metrics against the ground truth voxel-wise segmentation produced for a 3D MR image by specialists, who also confirmed the reconstruction accuracy qualitatively. KneeBones3Dify and annotated data are publicly available, enabling broader research and clinical practice use.
2024
27
0
0
Goal 3: Good health and well-being
Maddalena Lucia; Romano Diego; Gregoretti Francesco; De Lucia Gianluca; Antonelli Laura; Soscia Ernesto; Pontillo Gabriele; Langella Carla; Fazioli Fl...espandi
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1410461
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