A novel featureless approach to mass detection in digital mammograms based on support vector machines.
In this work, we present a novel approach to mass detection in digital mammograms. The great variability of the appearance of masses is the main obstacle to building a mass detection method. It is indeed demanding to characterize all the varieties of masses with a reduced set of features. Hence, in our approach we have chosen not to extract any feature, for the detection of the region of interest; in contrast, we exploit all the information available on the image. A multiresolution overcomplete wavelet representation is performed, in order to codify the image with redundancy of information. The vectors of the very-large space obtained are then provided to a first support vector machine (SVM) classifier. The detection task is considered here as a two-class pattern recognition problem: crops are classified as suspect or not, by using this SVM classifier. False candidates are eliminated with a second cascaded SVM. To further reduce the number of false positives, an ensemble of experts is applied: the final suspect regions are achieved by using a voting strategy. The sensitivity of the presented system is nearly 80% with a false-positive rate of 1.1 marks per image, estimated on images coming from the USF DDSM database.
Campanini
Renato
R
Department of Physics, University of Bologna, and INFN, Bologna, Italy.
Dongiovanni
Danilo
D
Iampieri
Emiro
E
Lanconelli
Nico
N
Masotti
Matteo
M
Palermo
Giuseppe
G
Riccardi
Alessandro
A
Roffilli
Matteo
M
D000465:Algorithms; D001185:Artificial Intelligence; D001943:Breast Neoplasms / Q000145:classification / Q000000981:diagnostic imaging*; D016000:Cluster Analysis; D003205:Computing Methodologies; D005103:Expert Systems; D005189:False Positive Reactions; D005260:Female; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D008327:Mammography / Q000379:methods*; D010363:Pattern Recognition, Automated; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted