Name
Title | ||
|---|---|---|
Quantification of ultrasonic texture intra-heterogeneity via volumetric stochastic modeling for tissue characterization. |
Abstract | ||
|---|---|---|
•A new approach for assessing subtle heterogeneities within a given mass is proposed.•Volumetric Nakagami-based shape and scale parameters are estimated from ultrasound RF.•A multi-resolution Daubechies wavelet packet transform is performed adaptively.•Local multi-scale textural fractal descriptors are extracted from volumetric patches.•Results show improved prediction of therapy response and disease characterization. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.media.2014.12.004 | Medical Image Analysis |
Keywords | Field | DocType |
Texture analysis,Fractal dimension,Tumor characterization,Nakagami modeling,Ultrasound imaging | Voxel,Computer vision,Ultrasonic sensor,Pattern recognition,Speckle pattern,Fractal dimension,Image texture,Fractal,Nakagami distribution,Artificial intelligence,Mathematics,Spatial frequency | Journal |
Volume | Issue | ISSN |
21 | 1 | 1361-8415 |
Citations | PageRank | References |
7 | 0.52 | 14 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Omar S. Al-Kadi | 1 | 32 | 4.32 |
| Daniel Y F Chung | 2 | 7 | 0.86 |
| Robert C Carlisle | 3 | 7 | 0.86 |
| Constantin C Coussios | 4 | 7 | 0.86 |
| J. Alison Noble | 5 | 58 | 6.52 |