Utilize este identificador para referenciar este registo: http://hdl.handle.net/10451/53385
Registo completo
Campo DCValorIdioma
degois.publication.firstPage8265pt_PT
degois.publication.issue24pt_PT
degois.publication.titleSensorspt_PT
dc.contributor.authorPelicano, Ana Catarina-
dc.contributor.authorGonçalves, Maria C. T.-
dc.contributor.authorGodinho, Daniela M.-
dc.contributor.authorCastela, Tiago-
dc.contributor.authorOrvalho, M. Lurdes-
dc.contributor.authorAraújo, Nuno A. M.-
dc.contributor.authorPorter, Emily-
dc.contributor.authorConceição, Raquel C.-
dc.date.accessioned2022-06-14T22:06:39Z-
dc.date.available2022-06-14T22:06:39Z-
dc.date.issued2021-
dc.identifier.urihttp://hdl.handle.net/10451/53385-
dc.description.abstractBreast cancer diagnosis using radar-based medical MicroWave Imaging (MWI) has been studied in recent years. Realistic numerical and physical models of the breast are needed for simulation and experimental testing of MWI prototypes. We aim to provide the scientific community with an online repository of multiple accurate realistic breast tissue models derived from Magnetic Resonance Imaging (MRI), including benign and malignant tumours. Such models are suitable for 3D printing, leveraging experimental MWI testing. We propose a pre-processing pipeline, which includes image registration, bias field correction, data normalisation, background subtraction, and median filtering. We segmented the fat tissue with the region growing algorithm in fat-weighted Dixon images. Skin, fibroglandular tissue, and the chest wall boundary were segmented from water-weighted Dixon images. Then, we applied a 3D region growing and Hoshen-Kopelman algorithms for tumour segmentation. The developed semi-automatic segmentation procedure is suitable to segment tissues with a varying level of heterogeneity regarding voxel intensity. Two accurate breast models with benign and malignant tumours, with dielectric properties at 3, 6, and 9 GHz frequencies have been made available to the research community. These are suitable for microwave diagnosis, i.e., imaging and classification, and can be easily adapted to other imaging modalities.pt_PT
dc.language.isoengpt_PT
dc.relationFundação para a Ciência e Tecnologia (FCT) under the fellowship UI/BD/150762/2020pt_PT
dc.relationFundação para a Ciência e Tecnologia (FCT) under the fellowship 021.07228.BDpt_PT
dc.relationFundação para a Ciência e Tecnologia (FCT) under the Strategic Program UIDB/00645/2020pt_PT
dc.relationFundação para a Ciência e Tecnologia (FCT) under the Strategic Program UIDP/00645/2020pt_PT
dc.relationFundação para a Ciência e Tecnologia (FCT) under the Contract no. PTDC/FIS-MAC/28146/2017 (LISBOA-01-0145-FEDER-028146)pt_PT
dc.relationFundação para a Ciência e Tecnologia (FCT) under the Contract no. UIDB/00618/2020pt_PT
dc.relationFundação para a Ciência e Tecnologia (FCT) under the Contract no. UIDP/00618/2020pt_PT
dc.rightsopenAccesspt_PT
dc.subjectrealistic numerical modelspt_PT
dc.subjectbreast tumour modelspt_PT
dc.subjectdielectric propertiespt_PT
dc.subjectimage segmentationpt_PT
dc.subjectbreast model repository for microwave diagnosispt_PT
dc.titleDevelopment of 3D MRI-Based Anatomically Realistic Models of Breast Tissues and Tumours for Microwave Imaging Diagnosispt_PT
dc.typearticlept_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.peerreviewedyespt_PT
degois.publication.volume21pt_PT
dc.identifier.doi10.3390/s21248265pt_PT
Aparece nas colecções:IBEB - Artigos em Revistas Internacionais

Ficheiros deste registo:
Ficheiro Descrição TamanhoFormato 
sensors-21-08265-v2.pdf8,31 MBAdobe PDFVer/Abrir


FacebookTwitterDeliciousLinkedInDiggGoogle BookmarksMySpace
Formato BibTex MendeleyEndnote 

Todos os registos no repositório estão protegidos por leis de copyright, com todos os direitos reservados.