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Breast Shape Parametrization Through Planar Projections

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10016))

Abstract

In the last years, 3D scanning has replaced the low tech approach to acquire direct anthropometric measurements. These new methodologies provide a detailed digital model of the body and allow analysis of more complex information like volume, shape, curvature, and so on. The possibility to acquire the shape of soft tissues, such as the female human breast, has attracted the interest breast surgery specialists. The main aim of this work is to propose an innovative strategy to automatically analyze 3D breast shape in order to describe them within a quantitative well defined framework. In particular we propose a scanning procedure for a proper acquisition of breast surfaces by using the handheld scanner Structure Sensor, as well as a framework to process 3D digital data to extract the shape information. The proposed method consists in two main parts: firstly, the acquired digital 3D surfaces are projected in a 2D space and a set of 17 geometrical landmarks are extracted; then by exploiting Thin Plate Splines and Principal Components Analysis the original data are summarised and the breast shape is described by a small set of numerical parameters.

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Acknowledgment

The authors would like to thank the “Azienda Ospedaliera Cannizzaro”, the “Associazione Santantonese per la lotta ai tumori (ASLT)” and the female volunteers for their contribution as models.

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Correspondence to Dario Allegra .

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Gallo, G., Allegra, D., Atani, Y.G., Milotta, F.L.M., Stanco, F., Catanuto, G. (2016). Breast Shape Parametrization Through Planar Projections. In: Blanc-Talon, J., Distante, C., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2016. Lecture Notes in Computer Science(), vol 10016. Springer, Cham. https://doi.org/10.1007/978-3-319-48680-2_13

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  • DOI: https://doi.org/10.1007/978-3-319-48680-2_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48679-6

  • Online ISBN: 978-3-319-48680-2

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