Title :
Characterizing time-intensity curves for spectral morphometric analysis of intratumoral enhancement patterns in breast DCE-MRI: Comparison between differentiation performance of temporal model parameters based on DFT and SVD
Author :
Lee, Sang Ho ; Kim, Jong Hyo ; Park, Jeong Seon ; Jung, Yun Sub ; Moon, Woo Kyung
Author_Institution :
Interdiscipl. Program in Radiat. Appl. Life Sci., Seoul Nat. Univ., Seoul, South Korea
fDate :
June 28 2009-July 1 2009
Abstract :
This study was designed to characterize the spatio-temporal properties of intratumoral enhancement patterns by using voxel-wise temporal enhancement spectra and morphometry of their spatial distributions in dynamic contrast-enhanced (DCE) breast MRI. Discrete Fourier transformation (DFT) and singular value decomposition (SVD) were used to extract the temporal enhancement features for comparison, generating 4D spectral maps. The spatial variations of DFT and SVD-based eigen spectra within tumor were captured by 3D moment descriptors, respectively. Differentiation between benign and malignant tumors was carried out using least squares support vector machine (LS-SVM) with a radial basis function (RBF) kernel and leave-one-out cross validation was used for performance evaluation. Using DFT, the sensitivity, specificity and area under ROC curve were 84.8%, 64.4% and 0.728. Using SVD, the corresponding values were 100%, 86.7% and 0.935. Combination of SVD and 3D moments yields higher performance in tumor differentiation than that of DFT and 3D moments.
Keywords :
biomedical MRI; cancer; discrete Fourier transforms; image segmentation; least squares approximations; medical image processing; singular value decomposition; spatiotemporal phenomena; spectral analysis; support vector machines; tumours; 3D moment descriptors; 4D spectral maps; benign tumors; breast; discrete Fourier transformation; dynamic contrast-enhanced MRI; image segmentation; intratumoral enhancement patterns; least squares support vector machine; leave-one-out cross validation; malignant tumors; radial basis function kernel; singular value decomposition; spatial distributions; spatio-temporal properties; spectral morphometric analysis; time-intensity curves; voxel-wise temporal enhancement spectra; Breast neoplasms; Discrete Fourier transforms; Least squares methods; Magnetic resonance imaging; Malignant tumors; Pattern analysis; Performance analysis; Singular value decomposition; Spectral analysis; Support vector machines; 3D moment descriptors; Breast DCE-MRI; discrete Fourier transformation (DFT); singular value decomposition (SVD); spatio-temporal properties; tumor characterization;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-3931-7
Electronic_ISBN :
1945-7928
DOI :
10.1109/ISBI.2009.5192984