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Regarding "Segmentation of heterogeneous or small FDG PET positive tissue based on a 3D-locally adaptive random walk algorithm" By DP. Onoma et al., and . Comp. Med. Imag. and Graph., (2015)Conditional partial volume correction for emission tomography: A wavelet-based hidden Markov model and multi-resolution approach., , , , , , , and . ISBI, page 1319-1322. IEEE, (2008)Image Enhancement With PDEs and Nonconservative Advection Flow Fields., , , , , and . IEEE Trans. Image Processing, 28 (6): 3075-3088 (2019)Prognostic value of multimodal MRI tumor features in Glioblastoma multiforme using textural features analysis., , , , and . ISBI, page 50-54. IEEE, (2015)Non-stationary fuzzy Markov chain., , , and . Pattern Recognition Letters, 28 (16): 2201-2208 (2007)Image Change Detection Using Paradoxical Theory for Patient Follow-Up Quantitation and Therapy Assessment., , , , , , , and . IEEE Trans. Med. Imaging, 31 (9): 1743-1753 (2012)The first MICCAI challenge on PET tumor segmentation., , , , , , , , , and 11 other author(s). Medical Image Analysis, (2018)Incorporating Patient-Specific Variability in the Simulation of Realistic Whole-Body 18hboxF-FDG Distributions for Oncology Applications., , , , , , , and . Proceedings of the IEEE, 97 (12): 2026-2038 (2009)Reliability of PET/CT shape and heterogeneity features in functional and morphological components of Non-Small Cell Lung Cancer tumors: a repeatability analysis in a prospective multi-center cohort., , , , , , and . CoRR, (2016)A Fuzzy Locally Adaptive Bayesian Segmentation Approach for Volume Determination in PET., , , , and . IEEE Trans. Med. Imaging, 28 (6): 881-893 (2009)