Assessing the performance of morphological parameters in distinguishing breast tumors on ultrasound images.
This work aims at investigating seven morphological parameters in distinguishing malignant and benign breast tumors on ultrasound images. Linear discriminant analysis was applied to sets of up to five parameters and then the performances were assessed using the area Az (+/- standard error) under the ROC curve, accuracy (Ac), sensitivity (Se), specificity (Sp), positive predictive value and negative predictive value. The most relevant individual parameters were the normalized residual value (nrv) and overlap ratio (RS), both calculated from the convex polygon technique, and the circularity (C). When nrv and C were taken together with roughness (R), calculated from normalized radial length (NRL), a performance slightly over 83% in distinguishing malignant and benign breast tumors was achieved.
Alvarenga
André Victor
AV
Laboratory of Ultrasound, National Institute of Metrology, Standardization, and Industrial Quality (Inmetro), Av. N. Sra. das Gracas, 50 - Xerem, 25250-020 Duque de Caxias, Rio de Janeiro, Brazil. avalvarenga@inmetro.gov.br
Infantosi
Antonio Fernando C
AF
Pereira
Wagner Coelho A
WC
Azevedo
Carolina M
CM
D000465:Algorithms; D001185:Artificial Intelligence; D001331:Automation; D001499:Bayes Theorem; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods; D011237:Predictive Value of Tests; D012372:ROC Curve; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D016217:Ultrasonography, Mammary / Q000379:methods*