Name
Title | ||
|---|---|---|
Lesion Detection Using T1-Weighted Mri: A New Approach Based On Functional Cortical Rois |
Abstract | ||
|---|---|---|
Accurate and precise detection of brain lesions on MR images is important for relating lesion locations to impaired behaviors. In this paper, we propose a method to detect lesion voxels on each functional cortical ROI (Region of Interest) independently using only T1-weighted MR images (T1-MRI). In contrast to existing automatic lesion detection methods, which typically detect lesion voxels on the whole MR image or on gray matter (GM)/white matter (WM), we show that the proposed functional cortical ROI based method can lead to better lesion-detection performance. We evaluate the proposed method using an in-house dataset with 60 chronic stroke patients. Using leave-one-subject-out cross validation, the proposed method can achieve an average Dice coefficient of 0.74 +/- 0.11 and outperform three state-of-the-art methods by more than 0.05. |
Year | Venue | Keywords |
|---|---|---|
2017 | 2017 24TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | Lesion Detection, Functional Cortical ROIs, T1-weighted MRI, Stacked Autoencoder |
Field | DocType | ISSN |
Voxel,Pattern recognition,Lesion,White matter,Sørensen–Dice coefficient,Computer science,Image segmentation,Artificial intelligence,Region of interest,Cross-validation,Magnetic resonance imaging | Conference | 1522-4880 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dazhou Guo | 1 | 30 | 5.90 |
| Kang Zheng | 2 | 42 | 7.41 |
| Song Wang | 3 | 119 | 12.91 |