Manipulating patient data acquired by Computer tomography (CT), e.g., anatomical shape and geometry, as well as studying the biomedical devices used in patient care, is certainly of remarkable importance. Here, Medical Re- verse Engineering (MRE) and Rapid Prototyping (RP) play a key role in the 3D models reconstruction of patient anatomy, that can be exploit to make patient- specific, custom-made devices. The inherent variability of the human anatomy can be a problem, which is why the concept of custom-made devices is men- tioned. In this field, MRE exploits the computational tools provided by Statistical Shape Modelling (SSM) and Principal Component Analysis (PCA) to achieve computer modelling of 3D data from real models. The PCA is a statistical tool for reducing the number of variables in a population, while the SSM enables the development of an infinite digital population of a given anatomy. This paper aims to show the potential of SSM in the field of the MRE. The study will focus on the pathological lumbar spine. Here, SSM provides new pathological geometries of the lumbar spine, which can be extrapolated and used to produce customized biomedical devices for that given pathological deformation, as well as to perform Finite Element (FE) simulations. Therefore, utilising SSM can bring an addi- tional edge to MRE, due to the infinite population of CAD models of patient anatomy, which can be useful in the medical industry, as already pointed out. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Sciortino V., Ingrassia T., Cerniglia D., Pasta S. (2024). Statistical Shape Modelling as a Tool for Medical Reverse Engineering. In Statistical Shape Modelling as a Tool for Medical Reverse Engineering (pp. 215-223). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-52075-4_25].

Statistical Shape Modelling as a Tool for Medical Reverse Engineering

Sciortino V.
;
Ingrassia T.;Cerniglia D.;Pasta S.
2024-01-01

Abstract

Manipulating patient data acquired by Computer tomography (CT), e.g., anatomical shape and geometry, as well as studying the biomedical devices used in patient care, is certainly of remarkable importance. Here, Medical Re- verse Engineering (MRE) and Rapid Prototyping (RP) play a key role in the 3D models reconstruction of patient anatomy, that can be exploit to make patient- specific, custom-made devices. The inherent variability of the human anatomy can be a problem, which is why the concept of custom-made devices is men- tioned. In this field, MRE exploits the computational tools provided by Statistical Shape Modelling (SSM) and Principal Component Analysis (PCA) to achieve computer modelling of 3D data from real models. The PCA is a statistical tool for reducing the number of variables in a population, while the SSM enables the development of an infinite digital population of a given anatomy. This paper aims to show the potential of SSM in the field of the MRE. The study will focus on the pathological lumbar spine. Here, SSM provides new pathological geometries of the lumbar spine, which can be extrapolated and used to produce customized biomedical devices for that given pathological deformation, as well as to perform Finite Element (FE) simulations. Therefore, utilising SSM can bring an addi- tional edge to MRE, due to the infinite population of CAD models of patient anatomy, which can be useful in the medical industry, as already pointed out. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
2024
Settore ING-IND/15 - Disegno E Metodi Dell'Ingegneria Industriale
Settore ING-IND/14 - Progettazione Meccanica E Costruzione Di Macchine
Settore ING-IND/34 - Bioingegneria Industriale
9783031520747
9783031520754
Sciortino V., Ingrassia T., Cerniglia D., Pasta S. (2024). Statistical Shape Modelling as a Tool for Medical Reverse Engineering. In Statistical Shape Modelling as a Tool for Medical Reverse Engineering (pp. 215-223). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-52075-4_25].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/636093
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