A semi-empirical model for scatter field reduction in digital mammography

X-ray mammography is the gold standard technique in breast cancer screening programmes. One of the main challenges that mammography is still facing is scattered radiation, which degrades the quality of the image and complicates the diagnosis process. Anti-scatter grids, the main standard physical sc...

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Autores: Marimon Muñoz, Elena, Marsden, Phil A., Nait-Charif, Hammadi, Díaz, Oliver
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2021
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/190707
Acceso en línea:https://hdl.handle.net/2445/190707
Access Level:acceso abierto
Palabra clave:Mètode de Montecarlo
Diagnòstic per la imatge
Mamografia
Processament digital d'imatges
Monte Carlo method
Diagnostic imaging
Mammography
Digital image processing
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spelling A semi-empirical model for scatter field reduction in digital mammographyMarimon Muñoz, ElenaMarsden, Phil A.Nait-Charif, HammadiDíaz, OliverMètode de MontecarloDiagnòstic per la imatgeMamografiaProcessament digital d'imatgesMonte Carlo methodDiagnostic imagingMammographyDigital image processingX-ray mammography is the gold standard technique in breast cancer screening programmes. One of the main challenges that mammography is still facing is scattered radiation, which degrades the quality of the image and complicates the diagnosis process. Anti-scatter grids, the main standard physical scattering reduction technique, have some unresolved challenges as they increase the dose delivered to the patient, do not remove all the scattered radiation and increase the cost of the equipment. Alternative scattering reduction methods based on post-processing algorithms, have lately been under investigation. This study is concerned with the use of image post-processing to reduce the scatter contribution in the image, by convolving the primary plus scatter image with kernels obtained from simplified Monte Carlo (MC) simulations. The proposed semi-empirical approach uses up to five thickness-dependant symmetric kernels to accurately estimate the scatter contribution of different areas of the image. Single breast thickness-dependant kernels can over-estimate the scatter signal up to 60%, while kernels adapting to local variations have to be modified for each specific case adding high computational costs. The proposed method reduces the uncertainty to a 4%-10% range for a 35-70 mm breast thickness range, making it a very efficient, case-independent scatter modelling technique. To test the robustness of the method, the scattered corrected image has been successfully compared against full MC simulations for a range of breast thicknesses. In addition, clinical images of the 010A CIRS phantom were acquired with a mammography system with and without the presence of the anti-scatter grid. The grid-less images were post-processed and their quality was compared against the grid images, by evaluating the contrast-to-noise ratio and variance ratio using several test objects, which simulate calcifications and tumour masses. The results obtained show that the method reduces the scatter to similar levels than the anti-scatter grids.IOP Publishing2021info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttps://hdl.handle.net/2445/190707Articles publicats en revistes (Matemàtiques i Informàtica)reponame:Dipòsit Digital de la UBinstname:Universidad de BarcelonaInglésVersió postprint del document publicat a: https://doi.org/10.1088/1361-6560/abd231Physics in Medicine and Biology, 2021, vol. 66, num. 4https://doi.org/10.1088/1361-6560/abd231(c) IOP Publishing, 2021info:eu-repo/semantics/openAccessoai:diposit.ub.edu:2445/1907072026-05-27T06:46:51Z
dc.title.none.fl_str_mv A semi-empirical model for scatter field reduction in digital mammography
title A semi-empirical model for scatter field reduction in digital mammography
spellingShingle A semi-empirical model for scatter field reduction in digital mammography
Marimon Muñoz, Elena
Mètode de Montecarlo
Diagnòstic per la imatge
Mamografia
Processament digital d'imatges
Monte Carlo method
Diagnostic imaging
Mammography
Digital image processing
title_short A semi-empirical model for scatter field reduction in digital mammography
title_full A semi-empirical model for scatter field reduction in digital mammography
title_fullStr A semi-empirical model for scatter field reduction in digital mammography
title_full_unstemmed A semi-empirical model for scatter field reduction in digital mammography
title_sort A semi-empirical model for scatter field reduction in digital mammography
dc.creator.none.fl_str_mv Marimon Muñoz, Elena
Marsden, Phil A.
Nait-Charif, Hammadi
Díaz, Oliver
author Marimon Muñoz, Elena
author_facet Marimon Muñoz, Elena
Marsden, Phil A.
Nait-Charif, Hammadi
Díaz, Oliver
author_role author
author2 Marsden, Phil A.
Nait-Charif, Hammadi
Díaz, Oliver
author2_role author
author
author
dc.subject.none.fl_str_mv Mètode de Montecarlo
Diagnòstic per la imatge
Mamografia
Processament digital d'imatges
Monte Carlo method
Diagnostic imaging
Mammography
Digital image processing
topic Mètode de Montecarlo
Diagnòstic per la imatge
Mamografia
Processament digital d'imatges
Monte Carlo method
Diagnostic imaging
Mammography
Digital image processing
description X-ray mammography is the gold standard technique in breast cancer screening programmes. One of the main challenges that mammography is still facing is scattered radiation, which degrades the quality of the image and complicates the diagnosis process. Anti-scatter grids, the main standard physical scattering reduction technique, have some unresolved challenges as they increase the dose delivered to the patient, do not remove all the scattered radiation and increase the cost of the equipment. Alternative scattering reduction methods based on post-processing algorithms, have lately been under investigation. This study is concerned with the use of image post-processing to reduce the scatter contribution in the image, by convolving the primary plus scatter image with kernels obtained from simplified Monte Carlo (MC) simulations. The proposed semi-empirical approach uses up to five thickness-dependant symmetric kernels to accurately estimate the scatter contribution of different areas of the image. Single breast thickness-dependant kernels can over-estimate the scatter signal up to 60%, while kernels adapting to local variations have to be modified for each specific case adding high computational costs. The proposed method reduces the uncertainty to a 4%-10% range for a 35-70 mm breast thickness range, making it a very efficient, case-independent scatter modelling technique. To test the robustness of the method, the scattered corrected image has been successfully compared against full MC simulations for a range of breast thicknesses. In addition, clinical images of the 010A CIRS phantom were acquired with a mammography system with and without the presence of the anti-scatter grid. The grid-less images were post-processed and their quality was compared against the grid images, by evaluating the contrast-to-noise ratio and variance ratio using several test objects, which simulate calcifications and tumour masses. The results obtained show that the method reduces the scatter to similar levels than the anti-scatter grids.
publishDate 2021
dc.date.none.fl_str_mv 2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/190707
url https://hdl.handle.net/2445/190707
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Versió postprint del document publicat a: https://doi.org/10.1088/1361-6560/abd231
Physics in Medicine and Biology, 2021, vol. 66, num. 4
https://doi.org/10.1088/1361-6560/abd231
dc.rights.none.fl_str_mv (c) IOP Publishing, 2021
info:eu-repo/semantics/openAccess
rights_invalid_str_mv (c) IOP Publishing, 2021
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IOP Publishing
publisher.none.fl_str_mv IOP Publishing
dc.source.none.fl_str_mv Articles publicats en revistes (Matemàtiques i Informàtica)
reponame:Dipòsit Digital de la UB
instname:Universidad de Barcelona
instname_str Universidad de Barcelona
reponame_str Dipòsit Digital de la UB
collection Dipòsit Digital de la UB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301629

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