Name
Abstract | ||
|---|---|---|
In diffusion MRI, numerical biomarkers are usually calculated for research and clinical purposes as Generalized Fractional Anisotropy (GFA). Recently, more eloquent indices allowing a more accurate description of tissue microstructure were derived from the SHORE model. Under certain experimental conditions, such indices express the morphological properties of the compartments where spins diffuse. Evidence of the suitability of such indices as biomarkers for stroke was provided in a previous study based on diffusion spectrum imaging (DSI) and focusing on the cortical motor loop. The goal of this work was to investigate the suitability of such indices for stratification, namely for distinguishing pathological from healthy subjects. To this end, two different paths were followed. First, the same approach used in the previous work for longitudinal analysis (statistics-based) was applied to detect inter-group variations. Then, a new approach based on the LASSO regressor was proposed. Results provided evidence of the suitability of the proposed indices for stratification purposes. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ISBI.2016.7493457 | 2016 IEEE 13TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI) |
Keywords | Field | DocType |
Diffusion MRI, Classification, Stroke, Tractography, 3D-SHORE | Diffusion MRI,Pattern recognition,Diffusion Spectrum Imaging,Computer science,Fractional anisotropy,Lasso (statistics),Stroke,Biomarker (medicine),Shore,Artificial intelligence,Tractography | Conference |
ISSN | Citations | PageRank |
1945-7928 | 0 | 0.34 |
References | Authors | |
1 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Silvia Obertino | 1 | 0 | 0.34 |
| Lorenza Brusini | 2 | 9 | 3.58 |
| Ilaria Boscolo Galazzo | 3 | 5 | 5.13 |
| Mauro Zucchelli | 4 | 26 | 5.91 |
| Cristina Granziera | 5 | 7 | 1.81 |
| Marco Cristani | 6 | 0 | 0.34 |
| Gloria Menegaz | 7 | 75 | 10.73 |