Pectoral muscle removal in mammogram images: A novel approach for improved accuracy and efficiency.
Cancer Causes Control
; 35(1): 185-191, 2024 Jan.
Article
en En
| MEDLINE
| ID: mdl-37676616
ABSTRACT
PURPOSE:
Accurate pectoral muscle removal is critical in mammographic breast density estimation and many other computer-aided algorithms. We propose a novel approach to remove pectoral muscles form mediolateral oblique (MLO) view mammograms and compare accuracy and computational efficiency with existing method (Libra).METHODS:
A pectoral muscle identification pipeline was developed. The image is first binarized to enhance contrast and then the Canny algorithm was applied for edge detection. Robust interpolation is used to smooth out the pectoral muscle region. Accuracy and computational speed of pectoral muscle identification was assessed using 951 women (1,902 MLO mammograms) from the Joanne Knight Breast Health Cohort at Washington University School of Medicine.RESULTS:
Our proposed algorithm exhibits lower mean error of 12.22% in comparison to Libra's estimated error of 20.44%. This 40% gain in accuracy was statistically significant (p < 0.001). The computational time for the proposed algorithm is 5.4 times faster when compared to Libra (5.1 s for proposed vs. 27.7 s for Libra per mammogram).CONCLUSION:
We present a novel approach for pectoral muscle removal in mammogram images that demonstrates significant improvement in accuracy and efficiency compared to existing method. Our findings have important implications for the development of computer-aided systems and other automated tools in this field.Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Músculos Pectorales
/
Neoplasias de la Mama
Tipo de estudio:
Prognostic_studies
Límite:
Female
/
Humans
Idioma:
En
Revista:
Cancer Causes Control
Asunto de la revista:
EPIDEMIOLOGIA
/
NEOPLASIAS
Año:
2024
Tipo del documento:
Article
País de afiliación:
Estados Unidos