A Comparative Study of Breast Surface Reconstruction for Aesthetic Outcome Assessment

  • René M. LacherEmail author
  • Francisco Vasconcelos
  • David C. Bishop
  • Norman R. Williams
  • Mohammed Keshtgar
  • David J. Hawkes
  • John H. Hipwell
  • Danail Stoyanov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10434)


Breast cancer is the most prevalent cancer type in women, and while its survival rate is generally high the aesthetic outcome is an increasingly important factor when evaluating different treatment alternatives. 3D scanning and reconstruction techniques offer a flexible tool for building detailed and accurate 3D breast models that can be used both pre-operatively for surgical planning and post-operatively for aesthetic evaluation. This paper aims at comparing the accuracy of low-cost 3D scanning technologies with the significantly more expensive state-of-the-art 3D commercial scanners in the context of breast 3D reconstruction. We present results from 28 synthetic and clinical RGBD sequences, including 12 unique patients and an anthropomorphic phantom demonstrating the applicability of low-cost RGBD sensors to real clinical cases. Body deformation and homogeneous skin texture pose challenges to the studied reconstruction systems. Although these should be addressed appropriately if higher model quality is warranted, we observe that low-cost sensors are able to obtain valuable reconstructions comparable to the state-of-the-art within an error margin of 3 mm.


Aesthetic evaluation Depth cameras Breast cancer 



This work was supported by the EPSRC (EP/N013220/1, EP/N022750/1, EP/N027078/1, NS/A000027/1, EP/P012841/1), TheWellcome Trust (WT101957, 201080/Z/16/Z), the EU FP7 VPH-PICTURE (FP7-ICT-2011-9-600948) and Horizon2020 EndoVESPA project (H2020-ICT-2015-688592).


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • René M. Lacher
    • 1
    Email author
  • Francisco Vasconcelos
    • 1
  • David C. Bishop
    • 2
  • Norman R. Williams
    • 3
  • Mohammed Keshtgar
    • 4
  • David J. Hawkes
    • 1
  • John H. Hipwell
    • 1
  • Danail Stoyanov
    • 1
  1. 1.Centre for Medical Image ComputingUniversity College LondonLondonUK
  2. 2.Medical Photography, Royal Free and University College Medical SchoolLondonUK
  3. 3.Surgical and Interventional Trials UnitUniversity College LondonLondonUK
  4. 4.Royal Free London Foundation TrustLondonUK

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