K. Wu, Y. Ung, and D. Hwang, Autocontouring and Manual Contouring: Which Is the Better Method for Target Delineation Using 18F-FDG PET/CT in Non-Small Cell Lung Cancer?, Journal of Nuclear Medicine, vol.51, issue.10, pp.1517-1523, 2010.
DOI : 10.2967/jnumed.110.077974

K. Wu, Y. Ung, and J. Hornby, PET CT Thresholds for Radiotherapy Target Definition in Non???Small-Cell Lung Cancer: How Close Are We to the Pathologic Findings?, International Journal of Radiation Oncology*Biology*Physics, vol.77, issue.3, pp.699-706, 2010.
DOI : 10.1016/j.ijrobp.2009.05.028

J. Yu, X. Li, and L. Xing, Comparison of Tumor Volumes as Determined by Pathologic Examination and FDG-PET/CT Images of Non???Small-Cell Lung Cancer: A Pilot Study, International Journal of Radiation Oncology*Biology*Physics, vol.75, issue.5, pp.1468-1474, 2009.
DOI : 10.1016/j.ijrobp.2009.01.019

M. Hatt, A. Turzo, and C. Roux, A Fuzzy Locally Adaptive Bayesian Segmentation Approach for Volume Determination in PET, IEEE Transactions on Medical Imaging, vol.28, issue.6, pp.881-893, 2009.
DOI : 10.1109/TMI.2008.2012036
URL : https://hal.archives-ouvertes.fr/inserm-00372910

U. Nestle, S. Kremp, and A. Schaefer-schuler, Comparison of Different Methods for Delineation of 18F- FDG PET-Positive Tissue for Target Volume Definition in Radiotherapy of Patients with Non-Small Cell Lung Cancer, J. Nucl. Med, vol.46, issue.8, pp.1342-1350, 2005.

J. Daisne, M. Sibomana, and A. Bol, Tri-dimensional automatic segmentation of PET volumes based on measured source-to-background ratios: influence of reconstruction algorithms, Radiotherapy and Oncology, vol.69, issue.3, pp.247-250, 2003.
DOI : 10.1016/S0167-8140(03)00270-6

M. Hatt, C. Le-rest, C. Descourt, and P. , Accurate Automatic Delineation of Heterogeneous Functional Volumes in Positron Emission Tomography for Oncology Applications, International Journal of Radiation Oncology*Biology*Physics, vol.77, issue.1, pp.301-308, 2010.
DOI : 10.1016/j.ijrobp.2009.08.018
URL : https://hal.archives-ouvertes.fr/inserm-00537776

X. Geets, J. A. Lee, and A. Bol, A gradient-based method for segmenting FDG-PET images: methodology and validation, European Journal of Nuclear Medicine and Molecular Imaging, vol.10, issue.Suppl 2, pp.1427-1438, 2007.
DOI : 10.1007/s00259-006-0363-4

D. W. Montgomery, A. Amira, and H. Zaidi, Fully automated segmentation of oncological PET volumes using a combined multiscale and statistical model, Medical Physics, vol.3, issue.2, pp.722-736, 2007.
DOI : 10.1118/1.2432404

H. Yu, C. Caldwell, and K. Mah, Automated Radiation Targeting in Head-and-Neck Cancer Using Region-Based Texture Analysis of PET and CT Images, International Journal of Radiation Oncology*Biology*Physics, vol.75, issue.2, pp.618-625, 2009.
DOI : 10.1016/j.ijrobp.2009.04.043

M. Hatt, C. Le-rest, C. Aboagye, and E. , Reproducibility of 18F-FDG and 3'-Deoxy-3'-18F-Fluorothymidine PET Tumor Volume Measurements, Journal of Nuclear Medicine, vol.51, issue.9, pp.1368-1376, 2010.
DOI : 10.2967/jnumed.110.078501
URL : https://hal.archives-ouvertes.fr/inserm-00537774