An approach to the detection of lesions in mammograms using fuzzy image processing.
J Int Med Res
; 35(6): 790-5, 2007.
Article
em En
| MEDLINE
| ID: mdl-18034992
ABSTRACT
An algorithm was developed in this study, using rule-based fuzzy logic, to enable masses that are hard to recognize or detect in mammograms to become more readily perceptible. Small lesions, such as microcalcifications and other masses that are hard to recognize, especially on film scan mammograms, were processed through segmentation. A total of 40 mammograms were used and they were classified by radiologists into three groups those with microcalcifications (n=15), those with tumours (n=15), and those with no lesions (n=10). Five mammograms were taken as training data sets from each of the groups with microcalcifications and tumours. The algorithm was then applied to data not taken for training. The algorithm achieved a mean accuracy of 99% compared with the findings of the radiologists.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Neoplasias da Mama
/
Mamografia
/
Interpretação de Imagem Radiográfica Assistida por Computador
/
Intensificação de Imagem Radiográfica
/
Lógica Fuzzy
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
/
Screening_studies
Limite:
Female
/
Humans
Idioma:
En
Revista:
J Int Med Res
Ano de publicação:
2007
Tipo de documento:
Article
País de afiliação:
Turquia