Name
Abstract | ||
|---|---|---|
Zernike phase contrast is a technique useful for nano-scale Xray imaging of materials with a low absorption coefficient. It enhances the image contrast using a phase ring. However, it also creates artifacts that hinder the use of traditional techniques for X-ray computed tomography (CT) image segmentation. We propose an image restoration method that models the phase contrast optics and minimizes an energy function. Though similar techniques have been used for visible light microscopy, this method deals with more spacious samples using an effective edge detection method. This paper demonstrates the removal of artifacts in multiple slices of phase contrast X-ray CT images and the potential in using this technique to aid CT image segmentation. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-09994-1_28 | Computational Modeling of Objects Presented in Images: Fundamentals, Methods, and Applications |
Keywords | Field | DocType |
Nano scale X-ray computed tomography, phase contrast optics, image restoration, image segmentation | Attenuation coefficient,Computer vision,X-ray,Nanoscopic scale,Edge detection,Optics,Image segmentation,Zernike polynomials,Artificial intelligence,Microscopy,Image restoration,Materials science | Conference |
Volume | ISSN | Citations |
8641 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 1 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arjun Kumar | 1 | 0 | 0.34 |
| Pratiti Mandal | 2 | 0 | 0.34 |
| Yongjie Zhang | 3 | 293 | 34.45 |
| Shawn Litster | 4 | 0 | 0.34 |