| Original language | English |
|---|---|
| Pages (from-to) | 5835-5848 |
| Number of pages | 14 |
| Journal | Medical Physics |
| Volume | 44 |
| Issue number | 11 |
| DOIs | |
| Publication status | Published - Nov 2017 |
Keywords
- Bayesian inference
- computed tomography (CT)
- hidden Markov trees (HMT)
- positron emission tomography (PET)
- segmentation
- wavelet and contourlet analysis
- CELL LUNG-CANCER
- TUMOR DELINEATION
- F-18-FDG PET
- CT IMAGES
- TRACER UPTAKE
- MODEL
- RECONSTRUCTION
- BRAIN
- CLASSIFICATION
- QUANTITATION
Cite this
}
A framework based on hidden Markov trees for multimodal PET/CT image co-segmentation. / Hanzouli-Ben Salah, Houda; Lapuyade-Lahorgue, Jerome; Bert, Julien; Benoit, Didier; Lambin, Philippe; Van Baardwijk, Angela; Monfrini, Emmanuel; Pieczynski, Wojciech; Visvikis, Dimitris; Hatt, Mathieu.
In: Medical Physics, Vol. 44, No. 11, 11.2017, p. 5835-5848.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - A framework based on hidden Markov trees for multimodal PET/CT image co-segmentation
AU - Hanzouli-Ben Salah, Houda
AU - Lapuyade-Lahorgue, Jerome
AU - Bert, Julien
AU - Benoit, Didier
AU - Lambin, Philippe
AU - Van Baardwijk, Angela
AU - Monfrini, Emmanuel
AU - Pieczynski, Wojciech
AU - Visvikis, Dimitris
AU - Hatt, Mathieu
PY - 2017/11
Y1 - 2017/11
KW - Bayesian inference
KW - computed tomography (CT)
KW - hidden Markov trees (HMT)
KW - positron emission tomography (PET)
KW - segmentation
KW - wavelet and contourlet analysis
KW - CELL LUNG-CANCER
KW - TUMOR DELINEATION
KW - F-18-FDG PET
KW - CT IMAGES
KW - TRACER UPTAKE
KW - MODEL
KW - RECONSTRUCTION
KW - BRAIN
KW - CLASSIFICATION
KW - QUANTITATION
U2 - 10.1002/mp.12531
DO - 10.1002/mp.12531
M3 - Article
VL - 44
SP - 5835
EP - 5848
JO - Medical Physics
JF - Medical Physics
SN - 0094-2405
IS - 11
ER -