Name
Title | ||
|---|---|---|
Segmentation of heterogeneous or small FDG PET positive tissue based on a 3D-locally adaptive random walk algorithm. |
Abstract | ||
|---|---|---|
•We propose to use the distance between adjacent nodes in place of a constant β parameter to take into account the different distances between adjacent nodes in 26 connectivity.•To reduce the partial volume effect in PET imaging, we propose to strengthen the grouping of voxels having similar intensity by adding the likelihood of probability to each class (tumor and non-tumor).•The accuracy in the small and heteregenous tumor segmentation is improved using our improvements. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.compmedimag.2014.09.007 | Computerized Medical Imaging and Graphics |
Keywords | DocType | Volume |
Random walk,PET imaging,Tumor segmentation,Heterogeneous tumors | Journal | 38 |
Issue | ISSN | Citations |
8 | 0895-6111 | 10 |
PageRank | References | Authors |
0.71 | 8 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| D P Onoma | 1 | 10 | 0.71 |
| Ruan Su | 2 | 559 | 53.00 |
| S Thureau | 3 | 10 | 0.71 |
| L Nkhali | 4 | 10 | 1.04 |
| Romain Modzelewski | 5 | 43 | 3.52 |
| G A Monnehan | 6 | 10 | 0.71 |
| Pierre Vera | 7 | 59 | 10.15 |
| Isabelle Gardin | 8 | 31 | 4.55 |