Name
Title | ||
|---|---|---|
CT liver tumor segmentation hybrid approach using neutrosophic sets, fast fuzzy c-means and adaptive watershed algorithm. |
Abstract | ||
|---|---|---|
•Hybrid approach based on NS, Watershed, and fast FCM algorithms for automatic CT liver tumor segmentation.•Results demonstrate that, neutrosophy can handle indeterminacy, uncertainty, and reduce over-segmentation.•The over-all accuracy obtained from the proposed approach almost 95% of good liver segmentation.•This results can help for further diagnosis and treatment planning. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.artmed.2018.11.007 | Artificial Intelligence in Medicine |
Field | DocType | Volume |
Data mining,Median filter,Pattern recognition,Segmentation,Computer science,Fuzzy logic,Watershed,Artificial intelligence,Connected component,Pixel,Cluster analysis,Histogram equalization | Journal | 97 |
ISSN | Citations | PageRank |
0933-3657 | 1 | 0.35 |
References | Authors | |
17 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ahmed M. Anter | 1 | 44 | 7.37 |
| Aboul Ella Hassenian | 2 | 10 | 1.22 |