Title :
Significance of MPEG-7 Textural Features for Improved Mass Detection in Mammography
Author :
Eltonsy, Nevine H. ; Tourassi, Georgia D. ; Fadeev, Aleksey ; Elmaghraby, Adel S.
Author_Institution :
Louisville Univ., KY
fDate :
Aug. 30 2006-Sept. 3 2006
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=0.85plusmn0.01. The MPEG-7 edge histogram descriptor-based BPNN showed an ROC area index of Az=0.71plusmn0.01 while homogeneous textural descriptors using 30 and 120 channels helped the BPNN achieve similar ROC area indexes of Az=0.882plusmn0.02 and Az=0.877plusmn0.01 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=0.91plusmn0.01. MPEG-7 homogeneous textural descriptor significantly improved the morphology-based detection scheme
Keywords :
backpropagation; biological organs; cancer; content-based retrieval; feature extraction; image texture; mammography; medical image processing; neural nets; sensitivity analysis; statistical analysis; tumours; MPEG-7 textural features; ROC area index; back-propagation artificial neural network; cancer regions; content-based image retrieval systems; edge histogram descriptor-based BPNN; homogeneous textural descriptor; leave-one-out sampling scheme; mammographic masses detection; morphological directional neighborhood features extraction; normal parenchyma; receiver operating characteristics; Artificial neural networks; Cancer; Feature extraction; Histograms; MPEG 7 Standard; Mammography; Merging; Performance evaluation; Sampling methods; Spatial databases; Computer Assisted Detection (CAD); MPEG-7 textural descriptors; malignant masses; morphological features;
Conference_Titel :
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location :
New York, NY
Print_ISBN :
1-4244-0032-5
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2006.260483