Abstract--Breast cancer is the most frequently diagnosed non-skin cancer in women, the second leading cause of death among women. Early detection of a breast cancer is fundamental for ensuring high survival rate. Imaging techniques are used to identify suspicious modifications of breast tissue. Among these, contrast-enhanced magnetic resonance imaging (CE-MRI) is particularly interesting for its lack of exposure to radiation and its ability to highlight differences in vascularisation, typical of cancer lesions. Automatic or semi-automatic methods are especially useful with this technique, due to the high quantity of data, in the form of 4D images (3D space + time), to be analysed in each test. This survey describes approaches to fully automatic computer-aided detection/diagnosis of breast lesions with CE-MRI, with particular emphasis on computational intelligence techniques.

Automatic Approaches for CE-MRI Examination of the Breast: A Survey

FA Cardillo;
2017

Abstract

Abstract--Breast cancer is the most frequently diagnosed non-skin cancer in women, the second leading cause of death among women. Early detection of a breast cancer is fundamental for ensuring high survival rate. Imaging techniques are used to identify suspicious modifications of breast tissue. Among these, contrast-enhanced magnetic resonance imaging (CE-MRI) is particularly interesting for its lack of exposure to radiation and its ability to highlight differences in vascularisation, typical of cancer lesions. Automatic or semi-automatic methods are especially useful with this technique, due to the high quantity of data, in the form of 4D images (3D space + time), to be analysed in each test. This survey describes approaches to fully automatic computer-aided detection/diagnosis of breast lesions with CE-MRI, with particular emphasis on computational intelligence techniques.
Campo DC Valore Lingua
dc.authority.people FA Cardillo it
dc.authority.people F Masulli it
dc.authority.people S Rovetta it
dc.collection.id.s 71c7200a-7c5f-4e83-8d57-d3d2ba88f40d *
dc.collection.name 04.01 Contributo in Atti di convegno *
dc.contributor.appartenenza Istituto di linguistica computazionale "Antonio Zampolli" - ILC *
dc.contributor.appartenenza.mi 918 *
dc.date.accessioned 2024/02/21 03:34:58 -
dc.date.available 2024/02/21 03:34:58 -
dc.date.issued 2017 -
dc.description.abstracteng Abstract--Breast cancer is the most frequently diagnosed non-skin cancer in women, the second leading cause of death among women. Early detection of a breast cancer is fundamental for ensuring high survival rate. Imaging techniques are used to identify suspicious modifications of breast tissue. Among these, contrast-enhanced magnetic resonance imaging (CE-MRI) is particularly interesting for its lack of exposure to radiation and its ability to highlight differences in vascularisation, typical of cancer lesions. Automatic or semi-automatic methods are especially useful with this technique, due to the high quantity of data, in the form of 4D images (3D space + time), to be analysed in each test. This survey describes approaches to fully automatic computer-aided detection/diagnosis of breast lesions with CE-MRI, with particular emphasis on computational intelligence techniques. -
dc.description.affiliations Istituto di Linguistica Computazionale, CNR, Pisa, Italia. DIBRIS, Università di Genova, Italia DIBRIS, Università di Genova, Italia -
dc.description.allpeople F.A. Cardillo; F. Masulli; S. Rovetta -
dc.description.allpeopleoriginal F.A. Cardillo, F. Masulli, S. Rovetta -
dc.description.fulltext none en
dc.description.numberofauthors 1 -
dc.identifier.uri https://hdl.handle.net/20.500.14243/339525 -
dc.language.iso eng -
dc.relation.conferencedate 21-23/06/2017 -
dc.relation.conferencename 10th IEEE International Conference on Cyber, Physical and Social Computing (CPSCom-2017) -
dc.relation.conferenceplace United Kingdom -
dc.subject.keywords medical image analysis -
dc.subject.keywords computational intelligence -
dc.subject.singlekeyword medical image analysis *
dc.subject.singlekeyword computational intelligence *
dc.title Automatic Approaches for CE-MRI Examination of the Breast: A Survey en
dc.type.driver info:eu-repo/semantics/conferenceObject -
dc.type.full 04 Contributo in convegno::04.01 Contributo in Atti di convegno it
dc.type.miur 273 -
dc.type.referee Sì, ma tipo non specificato -
dc.ugov.descaux1 382552 -
iris.orcid.lastModifiedDate 2024/02/22 18:21:58 *
iris.orcid.lastModifiedMillisecond 1708622518579 *
iris.sitodocente.maxattempts 1 -
Appare nelle tipologie: 04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/339525
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