Name
Abstract | ||
|---|---|---|
The analysis of medical images, such as Computed Tomography (CT) Images, increasingly requires an automatic processing for region enhancement, segmentation, 3D reconstruction and many other purposes. This paper presents a framework for performing these tasks using partial differential equations in 3D images. From a set of partial differential equations, we obtain a method for noise reduction filtering with edge preservation, region enhancement through the discrimination of the relevant density values, contour refinement and 3D reconstruction. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/SITIS.2011.38 | SITIS |
Keywords | Field | DocType |
region enhancement,partial differential equations,contour refinement,edge preservation,automatic processing,computed tomography,partial differential equation,medical image,relevant density value,noise reduction,image segmentation,3d imaging,image reconstruction,3d reconstruction | Iterative reconstruction,Noise reduction,Computer vision,Pattern recognition,Segmentation,Computer science,Filter (signal processing),Image segmentation,Computed tomography,Artificial intelligence,Partial differential equation,3D reconstruction | Conference |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Miguel Alemán-Flores | 1 | 69 | 12.06 |
| Luis Alvarez | 2 | 0 | 0.34 |
| Patricia Alemán-Flores | 3 | 2 | 2.45 |
| Rafael Fuentes-Pavon | 4 | 0 | 0.34 |