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dc.contributor.authorToner, B.
dc.contributor.authorMakeev, A.
dc.contributor.authorQian, M.
dc.contributor.authorBadal, A.
dc.contributor.authorGlick, S.J.
dc.date.accessioned2021-07-16T01:36:41Z
dc.date.available2021-07-16T01:36:41Z
dc.date.issued2021
dc.identifier.citationToner, B., Makeev, A., Qian, M., Badal, A., & Glick, S. J. (2021, February). Classification of round lesions in dual-energy FFDM using a convolutional neural network: simulation study. In Medical Imaging 2021: Physics of Medical Imaging (Vol. 11595, p. 115952C). International Society for Optics and Photonics.
dc.identifier.isbn9781510000000
dc.identifier.issn1605-7422
dc.identifier.doi10.1117/12.2582301
dc.identifier.urihttp://hdl.handle.net/10150/660568
dc.description.abstractThe presence of round cystic and solid mass lesions identified at mammogram screenings account for a large number of recalls. These recalls can cause undue patient anxiety and increased healthcare costs. Since cystic masses are nearly always benign, accurate classification of these lesions would be allow a significant reduction in recalls. This classification is very difficult using conventional mammogram screening data, but this study explores the possibility of performing the task on dual-energy full field digital mammography (FFDM) data. Since clinical data of this type is not readily available, realistic simulated data with different sources of variation are used. With this data, a deep convolutional neural network (CNN) was trained and evaluated. It achieved an AUC of 0.980 and 42% specificity at the 99% sensitivity level. These promising results should motivate further development of such imaging systems. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
dc.language.isoen
dc.publisherSPIE
dc.rightsCopyright © 2021 SPIE.
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.titleClassification of round lesions in dual-energy ffdm using a convolutional neural network: Simulation study
dc.typeProceedings
dc.typetext
dc.contributor.departmentUniversity of Arizona
dc.identifier.journalProgress in Biomedical Optics and Imaging - Proceedings of SPIE
dc.description.noteImmediate access
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
dc.eprint.versionFinal published version
dc.source.journaltitleProgress in Biomedical Optics and Imaging - Proceedings of SPIE
refterms.dateFOA2021-07-16T01:36:41Z


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