Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/6124
Título: INbreast: Toward a Full-field Digital Mammographic Database
Autor: Moreira, Inês C.
Amaral, Igor
Domingues, Inês
Cardoso, António
Cardoso, Maria João
Cardoso, Jaime S.
Palavras-chave: Mammographic database
computer-aided detection
computer-aided diagnosis
Data: Fev-2012
Editora: Elsevier
Citação: 2
Resumo: Rationale and Objectives Computer-aided detection and diagnosis (CAD) systems have been developed in the past two decades to assist radiologists in the detection and diagnosis of lesions seen on breast imaging exams, thus providing a second opinion. Mammographic databases play an important role in the development of algorithms aiming at the detection and diagnosis of mammary lesions. However, available databases often do not take into consideration all the requirements needed for research and study purposes. This article aims to present and detail a new mammographic database. Materials and Methods Images were acquired at a breast center located in a university hospital (Centro Hospitalar de S. João [CHSJ], Breast Centre, Porto) with the permission of the Portuguese National Committee of Data Protection and Hospital's Ethics Committee. MammoNovation Siemens full-field digital mammography, with a solid-state detector of amorphous selenium was used. Results The new database—INbreast—has a total of 115 cases (410 images) from which 90 cases are from women with both breasts affected (four images per case) and 25 cases are from mastectomy patients (two images per case). Several types of lesions (masses, calcifications, asymmetries, and distortions) were included. Accurate contours made by specialists are also provided in XML format. Conclusion The strengths of the actually presented database—INbreast—relies on the fact that it was built with full-field digital mammograms (in opposition to digitized mammograms), it presents a wide variability of cases, and is made publicly available together with precise annotations. We believe that this database can be a reference for future works centered or related to breast cancer imaging.
Peer review: yes
URI: http://hdl.handle.net/10400.22/6124
DOI: 10.1016/j.acra.2011.09.014
ISSN: 1076-6332
Versão do Editor: http://www.sciencedirect.com/science/article/pii/S107663321100451X
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