Automated detection of microcalcification clusters for digital breast tomosynthesis using projection data only: a preliminary study.
Med Phys
; 35(4): 1486-93, 2008 Apr.
Article
em En
| MEDLINE
| ID: mdl-18491543
ABSTRACT
Digital breast tomosynthesis (DBT) is a promising modality for breast imaging in which an anisotropic volume image of the breast is obtained. We present an algorithm for computerized detection of microcalcification clusters (MCCs) for DBT. This algorithm operates on the projection views only. Therefore it does not depend on reconstruction, and is computationally efficient. The algorithm was developed using a database of 30 image sets with microcalcifications, and a control group of 30 image sets without visible findings. The patient data were acquired on the first DBT prototype at Massachusetts General Hospital. Algorithm sensitivity was estimated to be 0.86 at 1.3 false positive clusters, which is below that of current MCC detection algorithms for full-field digital mammography. Because of the small number of patient cases, algorithm parameters were not optimized and one linear classifier was used. An actual limitation of our approach may be that the signal-to-noise ratio in the projection images is too low for microcalcification detection. Furthermore, the database consisted of predominantly small MCC. This may be related to the image quality obtained with this first prototype.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Doenças Mamárias
/
Calcinose
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Reconhecimento Automatizado de Padrão
/
Mamografia
/
Interpretação de Imagem Radiográfica Assistida por Computador
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Intensificação de Imagem Radiográfica
/
Tomografia Computadorizada de Feixe Cônico
Tipo de estudo:
Diagnostic_studies
/
Evaluation_studies
Limite:
Humans
Idioma:
En
Revista:
Med Phys
Ano de publicação:
2008
Tipo de documento:
Article
País de afiliação:
Estados Unidos