Please use this identifier to cite or link to this item:
http://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/1457
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor | 268446 | es_ES |
dc.contributor | 49237 | es_ES |
dc.contributor.other | https://orcid.org/0000-0002-9498-6602 | - |
dc.contributor.other | https://orcid.org/0000-0002-7635-4687 | - |
dc.coverage.spatial | Global | es_ES |
dc.creator | Celaya Padilla, José María | - |
dc.creator | Guzmán Valdivia, César Humberto | - |
dc.creator | Galván Tejada, Jorge Issac | - |
dc.creator | Galván Tejada, Carlos Eric | - |
dc.creator | Gamboa Rosales, Hamurabi | - |
dc.creator | Delgado Contreras, Juan Rubén | - |
dc.creator | Martinez Torteya, Antonio | - |
dc.creator | Olivera Reyna, Roberto | - |
dc.creator | Manjarrez Sánchez, Jorge Roberto | - |
dc.creator | Martínez Ruíz, Francisco Javier | - |
dc.creator | Garza Veloz, Idalia | - |
dc.creator | Martínez Fierro, Margarita de la Luz | - |
dc.creator | Traviño, Victor | - |
dc.creator | Tamez Peña, José Gerardo | - |
dc.date.accessioned | 2020-03-24T20:26:23Z | - |
dc.date.available | 2020-03-24T20:26:23Z | - |
dc.date.issued | 2017-10-04 | - |
dc.identifier | info:eu-repo/semantics/publishedVersion | es_ES |
dc.identifier.isbn | 978-953-51-3558-6 | es_ES |
dc.identifier.uri | http://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/1457 | - |
dc.description.abstract | Breast cancer is one of the global leading causes of death among women, and an early detection is of uttermost importance to reduce mortality rates. Screening mammograms, in which radiologists rely only on their eyesight, are one of the most used early detection methods. However, characteristics, such as the asymmetry between breasts, a feature that could be very difficult to visually quantize, is key to breast cancer detection. Due to the highly heterogeneous and deformable structure of the breast itself, incorporating asymmetry measurements into an automated detection system is still a challenge. In this study, we proposed the use of a bilateral registration algorithm as an effective way to automatically measure mirror asymmetry. Furthermore, this information was fed to a machine learning algorithm to improve the accuracy of the model. In this study, 449 subjects (197 with calcifications, 207 with masses, and 45 healthy subjects) from a public database were used to train and evaluate the proposed methodology. Using this procedure, we were able to independently identify subjects with calcifications (accuracy = 0.825, AUC = 0.882) and masses (accuracy = 0.698, AUC = 0.807) from healthy subjects. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | IntechOpen | es_ES |
dc.relation | http://dx.doi.org/10.5772/intechopen.69526 | es_ES |
dc.relation.uri | generalPublic | es_ES |
dc.rights | Atribución-NoComercial-CompartirIgual 3.0 Estados Unidos de América | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/us/ | * |
dc.source | New Perspectives in Breast Imaging; Arshad M. Malikcoordinador. Reino Unido. p. 109-124 | es_ES |
dc.subject.classification | INGENIERIA Y TECNOLOGIA [7] | es_ES |
dc.subject.other | breast cancer | es_ES |
dc.subject.other | asymmetry | es_ES |
dc.subject.other | bilateral registration | es_ES |
dc.subject.other | CAD | es_ES |
dc.title | Incorporating Breast Asymmetry Studies into CADx Systems | es_ES |
dc.type | info:eu-repo/semantics/bookPart | es_ES |
Appears in Collections: | *Documentos Académicos*-- Doc. en Ing. y Tec. Aplicada |
Files in This Item:
File | Description | Size | Format | |
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Incorporating Breast Asymmetry Studies into CADx.pdf | 3,4 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License