Name
Abstract | ||
|---|---|---|
Minkowski Functionals (MFs) are geometric measurements of 3D shapes, including volume, surface area, curvature and Euler number. MFs can be used as texture descriptors for medical image analysis in the segmentation of normal anatomy as well as in the detection/diagnosis of pathology. In this paper, we propose a method for fast computation of MFs based on integral images, which offers significantly improved accuracy and efficiency compared with previous works. In addition, MFs computed using our method are used in applications on image segmentation and pathology detection. Our experiment results clearly demonstrate the potential of MFs in such medical image analysis tasks. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1117/12.912033 | Proceedings of SPIE |
Keywords | Field | DocType |
Minkowski Functionals,texture analysis,integral image,image segmentation | Euler number,Medical imaging,Image segmentation,Artificial intelligence,Computation,Computer vision,Mathematical optimization,Curvature,Pattern recognition,3d shapes,Segmentation,Minkowski space,Physics | Conference |
Volume | ISSN | Citations |
8314 | 0277-786X | 2 |
PageRank | References | Authors |
0.42 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| xiaoxing li | 1 | 2 | 0.42 |
| Paulo R. S. Mendonça | 2 | 610 | 50.38 |
| Rahul Bhotika | 3 | 142 | 17.94 |