Name
Abstract | ||
|---|---|---|
•We introduce a novel ANN segmentation approach for plantar fascia extraction and thickness estimation.•RBF-neural network is chosen in order to classify patches of the plantar fascia region.•Features ranking and selection techniques were also performed to obtain the best discriminatory features that define the PF region.•Can accurately estimate the thickness of the PF in different structures.•The effectiveness of the proposed method suggests that it has great potential for US imaging classification. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.compmedimag.2017.02.001 | Computerized Medical Imaging and Graphics |
Keywords | Field | DocType |
Ultrasound (US),Speckle noise,Plantar fascia (PF),Segmentation,Radial Basic Function Neural Network (RBF-NN),Feature extraction,Classification | Plantar fascia,Computer vision,Segmentation,Feature extraction,Artificial intelligence,Region of interest,Speckle noise,Artificial neural network,Thickening,Medicine,Ultrasound | Journal |
Volume | ISSN | Citations |
56 | 0895-6111 | 0 |
PageRank | References | Authors |
0.34 | 19 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Abdelhafid Boussouar | 1 | 0 | 0.68 |
| Farid Meziane | 2 | 308 | 37.98 |
| Gillian Crofts | 3 | 3 | 1.07 |