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Feasibility of Depth Sensors to Study Breast Deformation During Mammography Procedures

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Breast Imaging (IWDM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9699))

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Abstract

Virtual clinical trials (VCT) currently represent key tools for breast imaging optimisation, especially in two-dimensional planar mammography and digital breast tomosynthesis. Voxelised breast models are a crucial part of VCT as they allow the generation of synthetic image projections of breast tissue distribution. Therefore, realistic breast models containing an accurate representation of women breasts are needed. Current voxelised breast models show, in their compressed version, a very round contour which might not be representative of the entire population. This work pretends to develop an imaging framework, based on depth cameras, to investigate breast deformation during mammographic compression. Preliminary results show the feasibility of depth sensors for such task, however post-processing steps are needed to smooth the models. The proposed framework can be used in the future to produce more accurate compressed breast models, which will eventually generate more realistic images in VCT.

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Acknowledgments

This work is part of the SCARtool project (H2020-MSCA-IF-2014, reference 657875), a research funded by the European Union within the Marie Sklodowska-Curie Innovative Training Networks. Also, some of the authors have been partially supported from the Ministry of Economy and Competitiveness of Spain, under project references TIN2012-37171-C02-01 and DPI2015-68442-R, and the FPI grant BES-2013-065314. The authors would also like to thank radiographers at UDIAT for their help during image acquisition.

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Correspondence to Oliver Díaz .

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Díaz, O. et al. (2016). Feasibility of Depth Sensors to Study Breast Deformation During Mammography Procedures. In: Tingberg, A., Lång, K., Timberg, P. (eds) Breast Imaging. IWDM 2016. Lecture Notes in Computer Science(), vol 9699. Springer, Cham. https://doi.org/10.1007/978-3-319-41546-8_56

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  • DOI: https://doi.org/10.1007/978-3-319-41546-8_56

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-41545-1

  • Online ISBN: 978-3-319-41546-8

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