A Screening CAD Tool for the Detection of Microcalcification Clusters in Mammograms.
J Digit Imaging
; 32(5): 728-745, 2019 10.
Article
em En
| MEDLINE
| ID: mdl-31388866
ABSTRACT
Breast cancer is the most common cancer diagnosed in women worldwide. Up to 50% of non-palpable breast cancers are detected solely through microcalcification clusters in mammograms. This article presents a novel and completely automated algorithm for the detection of microcalcification clusters in a mammogram. A multiscale 2D non-linear energy operator is proposed for enhancing the contrast between the microcalcifications and the background. Several texture, shape, intensity, and histogram of oriented gradients (HOG)-based features are used to distinguish microcalcifications from other brighter mammogram regions. A new majority class data reduction technique based on data distribution is proposed to counter data imbalance problem. The algorithm is able to achieve 100% sensitivity with 2.59, 1.78, and 0.68 average false positives per image on Digital Database for Screening Mammography (scanned film), INbreast (direct radiography) database, and PGIMER-IITKGP mammogram (direct radiography) database, respectively. Thus, it might be used as a second reader as well as a screening tool to reduce the burden on radiologists.
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Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Neoplasias da Mama
/
Calcinose
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Mamografia
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Interpretação de Imagem Radiográfica Assistida por Computador
Tipo de estudo:
Diagnostic_studies
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Screening_studies
Limite:
Female
/
Humans
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article