Name
Abstract | ||
|---|---|---|
The paper describes a new method to segment ischemic stroke region on computed tomography (CT) images by utilizing joint features from mean, standard deviation, histogram, and gray level co-occurrence matrix methods. Presented unsupervised segmentation technique shows ability to segment ischemic stroke region. |
Year | Venue | Keywords |
|---|---|---|
2004 | Informatica, Lith. Acad. Sci. | ischemic stroke segmentation,gray level co-occurrence matrix,joint feature,computed tomography,presented unsupervised segmentation technique,segment ischemic stroke region,joint features,standard deviation,image segmentation.,new method,ischemic stroke of human head brain,image segmentation |
Field | DocType | Volume |
Stroke segmentation,Computer vision,Histogram,Computer science,Segmentation,Stroke,Image segmentation,Computed tomography,Gray level,Artificial intelligence,Standard deviation | Journal | 15 |
Issue | ISSN | Citations |
2 | 0868-4952 | 5 |
PageRank | References | Authors |
0.49 | 12 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrius Ušinskas | 1 | 6 | 1.54 |
| Romualdas A. Dobrovolskis | 2 | 5 | 0.49 |
| Bernd F. Tomandl | 3 | 19 | 1.68 |