Name
Title | ||
|---|---|---|
Semi-automatic lymphoma detection and segmentation using fully conditional random fields. |
Abstract | ||
|---|---|---|
•Fully Conditional Random Fields (CRF) are studied for the detection and segmentation of lymphoma from PET/CT.•Lymphomas can be everywhere in the body. CRF can model a large dependency in the hidden states.•The energy terms used in CRFs are estimated in an unsupervised way.•The results obtained over 11 patients are very encouraging. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.compmedimag.2018.09.001 | Computerized Medical Imaging and Graphics |
Keywords | Field | DocType |
Positron Emission Tomography (PET),Lymphoma detection and segmentation,Fully connected conditional random fields,Anatomical atlas | Conditional random field,False detection,Computer vision,Conditional probability,Segmentation,Positron emission tomography,Artificial intelligence,Dice,Medicine,Lymphoma,CRFS | Journal |
Volume | ISSN | Citations |
70 | 0895-6111 | 0 |
PageRank | References | Authors |
0.34 | 9 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuntao Yu | 1 | 0 | 0.68 |
| Pierre Decazes | 2 | 0 | 2.03 |
| Jérôme Lapuyade-Lahorgue | 3 | 2 | 2.39 |
| Isabelle Gardin | 4 | 31 | 4.55 |
| Pierre Vera | 5 | 59 | 10.15 |
| Ruan Su | 6 | 559 | 53.00 |