Name
Title | ||
|---|---|---|
Probabilistic Segmentation Of Brain White Matter Lesions Using Texture-Based Classification |
Abstract | ||
|---|---|---|
Lesions in brain white matter can cause significant functional deficits, and are often associated with neurological disease. The quantitative analysis of these lesions is typically performed manually by physicians on magnetic resonance images and represents a non-trivial, time-consuming and subjective task. The proposed method automatically segments white matter lesions using a probabilistic texture-based classification approach. It requires no parameters to be set, assumes nothing about lesion location, shape or size, and demonstrates better results (Dice coefficient of 0.84) when compared with other, similar published methods. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-59876-5_9 | IMAGE ANALYSIS AND RECOGNITION, ICIAR 2017 |
Keywords | Field | DocType |
White matter lesion (WML), Magnetic resonance (MR) imaging, Brain, Segmentation, Texture features | Computer vision,Lesion,Pattern recognition,Sørensen–Dice coefficient,Segmentation,Computer science,Artificial intelligence,Probabilistic logic,Brain White Matter,Hyperintensity,Probabilistic segmentation,Magnetic resonance imaging | Conference |
Volume | ISSN | Citations |
10317 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 6 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mariana P. Bento | 1 | 0 | 1.01 |
| Yan Sym | 2 | 0 | 0.34 |
| Richard Frayne | 3 | 39 | 8.71 |
| Roberto de Alencar Lotufo | 4 | 572 | 53.61 |
| Leticia Rittner | 5 | 82 | 12.95 |