| Literature DB >> 35146617 |
Abstract
3D modelling has been highlighted as one of the key digital technologies likely to impact surgical practice in the next decade. 3D virtual models are reconstructed using traditional 2D imaging data through either direct volume or indirect surface rendering. One of the principal benefits of 3D visualisation in surgery relates to improved anatomical understanding-particularly in cases involving highly variable complex structures or where precision is required.Workflows begin with imaging segmentation which is a key step in 3D reconstruction and is defined as the process of identifying and delineating structures of interest. Fully automated segmentation will be essential if 3D visualisation is to be feasibly incorporated into routine clinical workflows; however, most algorithmic solutions remain incomplete. 3D models must undergo a range of processing steps prior to visualisation, which typically include smoothing, decimation and colourization. Models used for illustrative purposes may undergo more advanced processing such as UV unwrapping, retopology and PBR texture mapping.Clinical applications are wide ranging and vary significantly between specialities. Beyond pure anatomical visualisation, 3D modelling offers new methods of interacting with imaging data; enabling patient-specific simulations/rehearsal, Computer-Aided Design (CAD) of custom implants/cutting guides and serves as the substrate for augmented reality (AR) enhanced navigation.3D may enable faster, safer surgery with reduced errors and complications, ultimately resulting in improved patient outcomes. However, the relative effectiveness of 3D visualisation remains poorly understood. Future research is needed to not only define the ideal application, specific user and optimal interface/platform for interacting with models but also identify means by which we can systematically evaluate the efficacy of 3D modelling in surgery.Entities:
Keywords: 3D-modelling; Segmentation; Surgery
Mesh:
Year: 2022 PMID: 35146617 DOI: 10.1007/978-3-030-87779-8_3
Source DB: PubMed Journal: Adv Exp Med Biol ISSN: 0065-2598 Impact factor: 2.622