We present a novel method to detect asymmetry in mammograms based upon bilateral analysis of the spatial distribution of density within paired mammographic strips. Various differential measures of spatial correlation of gray-scale values were computed with reference to the position of the nipple for a set of 128 pairs of mammograms from the Digital Database for Screening Mammography (DDSM). Features were selected by stepwise logistic regression and the leave-one-patient-out method was used for cross-validation of results. An area under the receiver operating characteristic curve of 0.87 (SE=0.08) was achieved by using an artificial neural network classifier with radial basis functions.
Casti, P., Mencattini, A., Salmeri, M., Rangayyan, R. (2014). Spatial correlation analysis of mammograms for detection of asymmetric findings. In Breast Imaging: 12th International Workshop, IWDM 2014, Gifu City, Japan, June 29 – July 2, 2014. Proceedings (pp.558-564). Hiroshi Fujita; Takeshi Hara; Chisako Muramatsu [10.1007/978-3-319-07887-8_78].
Spatial correlation analysis of mammograms for detection of asymmetric findings
Casti, P;MENCATTINI, ARIANNA;SALMERI, MARCELLO;
2014-06-01
Abstract
We present a novel method to detect asymmetry in mammograms based upon bilateral analysis of the spatial distribution of density within paired mammographic strips. Various differential measures of spatial correlation of gray-scale values were computed with reference to the position of the nipple for a set of 128 pairs of mammograms from the Digital Database for Screening Mammography (DDSM). Features were selected by stepwise logistic regression and the leave-one-patient-out method was used for cross-validation of results. An area under the receiver operating characteristic curve of 0.87 (SE=0.08) was achieved by using an artificial neural network classifier with radial basis functions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
