Name
Title | ||
|---|---|---|
Machine-Based Rejection of Low-Quality Spectra and Estimation of Brain Tumor Probabilities from Magnetic Resonance Spectroscopic Images |
Abstract | ||
|---|---|---|
Abstract: Magnetic resonance spectroscopic images (MRSI) carry spatiallyresolved information about the in vivo metabolism, however, theirevaluation is di#cult. Problems arise especially from artifacts and noise,yielding non-evaluable signals in many voxels. We propose a two-stepapproach to the processing of MRSI. In the first step a non-linear classifieris employed in every voxel to determine whether the spectral signalis evaluable, and if so, the tumor probability is computed in the second... |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/3-540-32137-3_7 | Bildverarbeitung für die Medizin |
Keywords | Field | DocType |
magnetic resonance spectroscopic imaging | Voxel,Magnetic resonance spectroscopic,Brain tumor,Spectral line,Magnetic resonance spectroscopic imaging,Classifier (linguistics),Nuclear magnetic resonance,Physics | Conference |
Citations | PageRank | References |
2 | 0.72 | 3 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bjoern H. Menze | 1 | 1032 | 80.31 |
| B. Michael Kelm | 2 | 255 | 15.41 |
| Daniel Heck | 3 | 58 | 2.58 |
| Matthias P. Lichy | 4 | 2 | 1.06 |
| Fred A. Hamprecht | 5 | 962 | 76.24 |