3D Visualisation of Skin Substitutes
Diagnosing skin diseases and researching the genesis of skin pathologies would substantially profit from sound topological information of the structures composing the layers of normal and pathologically transformed skin. Likewise, designing skin regenerat
- PDF / 722,953 Bytes
- 10 Pages / 439.37 x 666.14 pts Page_size
- 37 Downloads / 213 Views
3D Visualisation of Skin Substitutes W.J. Weninger, Lars-Peter Kamolz, and S.H. Geyer
8.1
Introduction
Diagnosing skin diseases and researching the genesis of skin pathologies would substantially profit from sound topological information of the structures composing the layers of normal and pathologically transformed skin. Likewise, designing skin regeneration material, improving its quality, and evaluating the transformation it undergoes after implantation require the precise visualisation of the architecture of this material and the three-dimensional (3D) arrangement of the cells and tissues populating it. Although the last decades saw the development of a great number of potent new 2D and 3D imaging techniques (Boppart et al. 1996; Kolker et al. 2000; Smith 2001; Sharpe et al. 2002; Sharpe 2003; Johnson et al. 2006; Weninger et al. 2006; Dodt et al. 2007; Filas et al. 2007; Wanninger 2007; Cavey and Lecuit 2008; Geyer et al. 2009; Metscher 2009; Mohun and Weninger 2011), high-quality 3D visualisation of skin architecture and skin replacement materials is still a major technical challenge. The basis for high-quality 3D visualisation is a digital volume data set. Volume data sets can be generated either by helical scanning of a specimen (as with computed tomography) or by stacking a series of digital images showing subsequent sections, which cut virtually or physically through a specimen (all other volume data generation techniques). Once a digital volume data set is generated, its content can be digitally processed and analysed three dimensionally with a broad variety of visualisation tools. Cutting user-defined virtual resection planes through the data volume is one possibility. Creating volume or surface-rendered computer models is another (Weninger and Geyer 2008). W.J. Weninger, MD (*) • S.H. Geyer, MD IMG, Centre for Anatomy and Cell Biology, Medical University of Vienna, Waehringer Str. 13, A-1090 Vienna, Austria e-mail: [email protected] L.-P. Kamolz, MD, MSc Division of Plastic, Aesthetic and Reconstructive Surgery, Research Unit for Tissue Regeneration, Repair and Reconstruction, Department of Surgery, Medical University of Graz, Graz, Austria L.-P. Kamolz, D.B. Lumenta (eds.), Dermal Replacements in General, Burn, and Plastic Surgery, DOI 10.1007/978-3-7091-1586-2_8, © Springer-Verlag Wien 2013
87
88
W.J. Weninger et al.
In principle, digital volume data can be generated with in vivo and in vitro (postmortem) imaging techniques. Volume data generated with in vivo imaging techniques, such as the computed tomography (CT), magnetic resonance tomography (MR) (Hogers et al. 2000; Ahrens et al. 2006; Bain et al. 2007; Deans et al. 2008) and 3D-ultrasound (3D-US) (Turnbull 1999; Meyer-Wittkopf et al. 2001; Mittermayer et al. 2004; Phoon 2006; Avni et al. 2007; Yagel et al. 2007), in vivo microscopy (Visscher 2010) and optical coherence tomography (OCT) (Männer et al. 2008; Norozi et al. 2008; Happel et al. 2011) would permit in situ analysis of skin and implanted skin replacement materi
Data Loading...
