title: Significance of MPEG-7 textural features for improved mass detection in mammography.
abstract: The purpose of the study is to investigate the significance of MPEG-7 textural features for improving the detection of masses in screening mammograms. The detection scheme was originally based on morphological directional neighborhood features extracted from mammographic regions of interest (ROIs). Receiver Operating Characteristics (ROC) was performed to evaluate the performance of each set of features independently and merged into a back-propagation artificial neural network (BPANN) using the leave-one-out sampling scheme (LOOSS). The study was based on a database of 668 mammographic ROIs (340 depicting cancer regions and 328 depicting normal parenchyma). Overall, the ROC area index of the BPANN using the directional morphological features was Az=0.85+/-0.01. The MPEG-7 edge histogram descriptor-based BPNN showed an ROC area index of Az=0.71+/-0.01 while homogeneous textural descriptors using 30 and 120 channels helped the BPNN achieve similar ROC area indexes of Az=0.882+/-0.02 and Az=0.877+/-0.01 respectively. After merging the MPEG-7 homogeneous textural features with the directional neighborhood features the performance of the BPANN increased providing an ROC area index of Az=0.91+/-0.01. MPEG-7 homogeneous textural descriptor significantly improved the morphology-based detection scheme.
authors.forename: Nevine H
authors.initials: NH
authors.lastname: Eltonsy
authors.forename: Georgia D
authors.initials: GD
authors.lastname: Tourassi
authors.forename: Aleksey
authors.initials: A
authors.lastname: Fadeev
authors.forename: Adel S
authors.initials: AS
authors.lastname: Elmaghraby
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging; D003201:Computers; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation* / Q000379:methods; D006801:Humans; D008327:Mammography / Q000295:instrumentation* / Q000379:methods*; D015233:Models, Statistical; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D011381:Programming Languages; D012372:ROC Curve; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000295:instrumentation* / Q000379:methods; D015203:Reproducibility of Results; D012984:Software