Feasibility of depth sensors to study breast deformation during mammography procedures
dc.contributor.author
dc.date.accessioned
2017-10-24T10:00:58Z
dc.date.available
2021-04-07T08:02:59Z
dc.date.issued
2016-01-01
dc.identifier.issn
0302-9743
dc.identifier.uri
dc.description.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
dc.description.sponsorship
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
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
Springer Verlag
dc.relation
info:eu-repo/grantAgreement/MINECO//TIN2012-37171-C02-01/ES/IA-BIOBREAST: ANALISIS TEMPORAL Y DETECCION AUTOMATICA DE LESIONES EN IMAGENES MULTIMODALES./
info:eu-repo/grantAgreement/MINECO//DPI2015-68442-R/ES/ANALISIS DE IMAGENES INTELIGENTE PARA LOS RETOS EN EL CRIBADO DE CANCER DE MAMA/
dc.relation.isformatof
Versió postprint del document publicat a: https://doi.org/10.1007/978-3-319-41546-8_56
dc.relation.ispartof
© Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, vol. 9699, p. 446-453
dc.relation.ispartofseries
Articles publicats (D-ATC)
dc.rights
Tots els drets reservats
dc.subject
dc.title
Feasibility of depth sensors to study breast deformation during mammography procedures
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.embargo.terms
2018-10-24T10:00:58Z
dc.relation.projectID
info:eu-repo/grantAgreement/EC/H2020/657875/EU/Scattered radiation reduction tool to improve computer-aided diagnosis performance in digital breast tomosynthesis/SCARtool
dc.type.version
info:eu-repo/semantics/acceptedVersion
dc.identifier.doi
dc.contributor.funder
dc.relation.FundingProgramme
dc.relation.ProjectAcronym
dc.identifier.eissn
1611-3349