Abstract Geographical information systems deal with spatial databases in which topological models are described with alphanumeric informa- tion. Its graphical interfaces implement the multilayer concept and provide powerful interaction tools. In this study, we apply these con- cepts to the human body creating a representation that would allow an interactive, precise, and detailed anatomical study. A vector surface component of the human body is built using a three-dimensional (3- D) reconstruction methodology. This multilayer concept is implement- ed by associating raster components with the corresponding vector surfaces, which include neighbourhood topology enabling spatial analysis. A root mean square error of 0.18 mm validated the three- dimensional reconstruction technique of internal anatomical struc- tures. The expansion of the identification and the development of a neighbourhood analysis function are the new tools provided in this model. Introduction Image segmentation is used in different areas and with different types of images. The segmentation of human body structures with red, green and blue (RGB) images has been the subject of research in sev- eral works (Schiemann et al., 1997; Pommert et al., 2001; Flores and Schmitt 2005; Liu et al., 2014) associated with the Visible Human Project (VHP) (http://www.nlm.nih.gov/research/visible/ animations.html) (Spitzer et al., 1996; Park et al., 2006; Zhang et al., 2006). Other methods, such as RGB cryosections (i.e. images slices), computed tomography (CT) and magnetic resonance imaging (MRI) use different combinations of image types included in these projects (Imielińska et al., 2000a, 2000b; Xue et al., 2014). The joint use of dif- ferent types of image for segmentation was chosen to take advantage of each format characteristics and to overcome identified, specific lim- itations. RGB images make available quite realistic information about the visual aspect of the anatomical structures. The quantity of stored information, larger than CT and MRI (Takanashi et al., 2002), enable a greater level of discrimination among these structures. However, RGB images present drawbacks when it comes to the delineate bones with articulations and/or tendons. In these cases, CT images are more efficient (Beylot et al., 1996). Regardless of the input data used, the segmentation procedures can be manual, semiautomatic or automatic. The automatic procedure cannot be considered when the segmentation needs a high level of detail and non-ambiguity is important (Schiemann et al., 1997; Beylot et al., 1996; Riemer et al., 2007). This occurs when a high level of qual- ity in the segmentation delineation is required to reconstruct the anatomical structures. The semiautomatic methods use the automatic components to facilitate and accelerate the segmentation procedure and the manual intervention to define parameters, correct errors and perform quality control (Schiemann et al., 1997; Takanashi et al., 2002; Imelińska et al., 2000a, 2000b; Beveridge et al., 2013). Geographical information systems (GIS) operate with spatial data models associated with alphanumeric information. Traditionally, these systems are more focused on the representation of objects more relat- ed to the Earth than anatomical features. However, the inclusion of human-body models in a GIS environment would greatly benefit from the characteristics of this approach to relate three-dimensional (3-D) structures to each other. Indeed, a GIS-based map of the vertebral canal was recently produced to spatially guide veterinary surgeons when evaluating extruded disc herniation in dogs, a common problem in this animal (Daraban et al., 2014). This work addresses two GIS characteristics: the multilayer concept and topology. The multilayer concept consists in structuring the infor- mation into layers and is implemented in the table of contents (TOC) of the interface. From the TOC, one can act independently over infor- mation layers to make them accessible to the operations to be carried out. Topology, on the other hand, concerns the study of the relation- ships among the spatial objects that compose the model. These rela- tionships can be obtained in two ways (Ellul and Haklay 2006): i) impromptu, the relationships among objects is determined when need- Correspondence: Antonio Barbeito, School of Technology and Management of Agueda, University of Aveiro, Apartado 473, 3754-909, Agueda, Portugal. Tel. +35.123.4611500. E-mail: amtb@ua.pt Key words: 3D GIS; Segmentation; Topology; Spatial analysis. Acknowledgements: the authors acknowledge the contribution of the U.S. National Library of Medicine for making available the datasets used in this work. Received for publication: 13 May 2015. Revision received: 27 August 2015. Accepted for publication: 30 August 2015. ©Copyright A. Barbeito et al., 2015 Licensee PAGEPress, Italy Geospatial Health 2015; 10:375 doi:10.4081/gh.2015.375 This article is distributed under the terms of the Creative Commons Attribution Noncommercial License (by-nc 3.0) which permits any noncom- mercial use, distribution, and reproduction in any medium, provided the orig- inal author(s) and source are credited. A topological multilayer model of the human body Antonio Barbeito, 1 Marco Painho, 2 Pedro Cabral, 2 João O’Neill 3 1 School of Technology and Management of Agueda, University of Aveiro, Agueda; 2 Nova Information Management School, Universidade Nova de Lisboa; 3 Department of Anatomy, Universidade Nova de Lisboa, Lisbon, Portugal [Geospatial Health 2015; 10:375] [page 199] Geospatial Health 2015; volume 10:375 Non commercial use only