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Comparison between two packages for pectoral muscle removal on mammographic images
- Source :
- La radiologia medica. 127:848-856
- Publication Year :
- 2022
- Publisher :
- Springer Science and Business Media LLC, 2022.
-
Abstract
- Background Pectoral muscle removal is a fundamental preliminary step in computer-aided diagnosis systems for full-field digital mammography (FFDM). Currently, two open-source publicly available packages (LIBRA and OpenBreast) provide algorithms for pectoral muscle removal within Matlab environment. Purpose To compare performance of the two packages on a single database of FFDM images. Methods Only mediolateral oblique (MLO) FFDM was considered because of large presence of pectoral muscle on this type of projection. For obtaining ground truth, pectoral muscle has been manually segmented by two radiologists in consensus. Both LIBRA’s and OpenBreast’s removal performance with respect to ground truth were compared using Dice similarity coefficient and Cohen-kappa reliability coefficient; Wilcoxon signed-rank test has been used for assessing differences in performances; Kruskal–Wallis test has been used to verify possible dependence of the performance from the breast density or image laterality. Results FFDMs from 168 consecutive women at our institution have been included in the study. Both LIBRA’s Dice-index and Cohen-kappa were significantly higher than OpenBreast (Wilcoxon signed-rank test P P > 0.05). Conclusion: Libra has a better performance than OpenBreast in pectoral muscle delineation so that, although our study has not a direct clinical application, these results are useful in the choice of packages for the development of complex systems for computer-aided breast evaluation.
- Subjects :
- Breast evaluation
Reproducibility of Result
Reproducibility of Results
Breast Neoplasms
General Medicine
Full-field digital mammography
Pectoralis Muscles
Algorithm
Radiographic Image Enhancement
Pectoral muscle removal
Humans
Radiographic Image Interpretation, Computer-Assisted
Female
Radiology, Nuclear Medicine and imaging
Breast Neoplasm
Algorithms
Human
Breast Density
Mammography
Subjects
Details
- ISSN :
- 18266983
- Volume :
- 127
- Database :
- OpenAIRE
- Journal :
- La radiologia medica
- Accession number :
- edsair.doi.dedup.....abaccf6f552e705fffe5af7314fc1487
- Full Text :
- https://doi.org/10.1007/s11547-022-01521-5