Name
Title | ||
|---|---|---|
Automatic myocardial ischemic lesion detection on magnetic resonance perfusion weighted imaging prior perfusion quantification: A pre-modeling strategy |
Abstract | ||
|---|---|---|
Even if cardiovascular magnetic resonance (CMR) perfusion imaging has proven its relevance for visual detection of ischemia, myocardial blood flow (MBF) quantification at the voxel observation scale remains challenging. Integration of an automated segmentation step, prior to perfusion index estimation, might be a significant reconstruction component that could allow sustainable assumptions and constraint enlargement prior to advanced modeling. Current clustering techniques, such as bullseye representation or manual delineation, are not designed to discriminate voxels belonging to the lesion from healthy areas. Hence, the resulting average time–intensity curve, which is assumed to represent the dynamic contrast enhancement inside of a lesion, might be contaminated by voxels with perfectly healthy microcirculation. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.compbiomed.2019.05.001 | Computers in Biology and Medicine |
Keywords | Field | DocType |
CMR,Spatio temporal region growing,Segmentation,Microcirculation,Myocardial perfusion,MR Cardiac Imaging,Heart diseases,Ischemic lesion | Voxel,Perfusion scanning,Biomedical engineering,Blood flow,Lesion,Pattern recognition,Segmentation,Computer science,Artificial intelligence,Cluster analysis,Magnetic resonance imaging,Perfusion | Journal |
Volume | ISSN | Citations |
110 | 0010-4825 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Clément Daviller | 1 | 0 | 0.68 |
| Thomas Grenier | 2 | 23 | 6.22 |
| Hélène Ratiney | 3 | 1 | 2.40 |
| Michaël Sdika | 4 | 81 | 9.17 |
| Pierre Croisille | 5 | 177 | 19.75 |
| Magalie Viallon | 6 | 12 | 3.65 |