Name
Abstract | ||
|---|---|---|
In this paper, a novel method is used for computerized lesion detection and analysis in three-dimensional(3D) contrast enhanced MR breast images. The automatic analysis involves three steps: 1) alignment between series; 2) extraction of suspicious regions; and 3) application of feature classification to each region. Assuming that there are only small geometric deformations after global registration, we adopted a 3D thin-plate spline based registration method, in which the control points are determined using 3D gradient and local correlation. Experiments show superior correlation between neighboring slices with 3D alignment as compared to a previous two-dimensional(2D) method. After registration, a new series named enhancement rate images(ERIs) are created. Suspicious volumes-of-interest(VOIs) are identified by 3D region labeling after thresholding the ERIs. Since carcinomas can typically be characterized by irregular borders and rapid and high uptake of contrast followed by a washout, a set of morphological features(irregularity, spiculation index, etc) and enhancement features(small volume enhancement rate, slope of average rate, etc) are calculated for selected VOIs and evaluated in a rule-based classifier to identify malignant lesions from benign lesions or normal tissues. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1117/12.431064 | Proceedings of SPIE |
Keywords | Field | DocType |
breast cancer,MR breast imaging,non-rigid registration,thin-plate spline | Spline (mathematics),Computer vision,Thin plate spline,Computer science,Artificial intelligence,Thresholding,Connected-component labeling,Classifier (linguistics),Eris | Conference |
Volume | ISSN | Citations |
4322 | 0277-786X | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| he wang | 1 | 15 | 11.58 |
| Bin Zheng | 2 | 135 | 28.83 |
| Walter F. Good | 3 | 78 | 15.30 |
| Xiao-Hui Wang | 4 | 67 | 16.97 |