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Brain tissue MR-image segmentation via optimum-path forest clustering., , , and . Computer Vision and Image Understanding, 116 (10): 1047-1059 (2012)Synergistic arc-weight estimation for interactive image segmentation using graphs., , and . Computer Vision and Image Understanding, 114 (1): 85-99 (2010)Erratum to multiscale skeletons by image foresting transform and its applications to neuromorphometry: Pattern Recognition 35(7) (2002) 1571-1582., , and . Pattern Recognition, 36 (12): 3013 (2003)A graph-based approach for multiscale shape analysis., , and . Pattern Recognition, 37 (6): 1163-1174 (2004)Cloud Bank: A Multiple Clouds Model and its Use in MR Brain Image Segmentation., , and . ISBI, page 506-509. IEEE, (2009)An Iterative Spanning Forest Framework for Superpixel Segmentation., , , , , and . IEEE Trans. Image Processing, 28 (7): 3477-3489 (2019)Visualizing Time-Dependent Data Using Dynamic t-SNE., , and . EuroVis (Short Papers), page 73-77. Eurographics Association, (2016)OPF-MRF: Optimum-Path Forest and Markov Random Fields for Contextual-Based Image Classification., , , , , and . CAIP (2), volume 8048 of Lecture Notes in Computer Science, page 233-240. Springer, (2013)Improving Parkinson's disease identification through evolutionary-based feature selection., , , , , and . EMBC, page 7857-7860. IEEE, (2011)Robust and fast Vowel Recognition Using Optimum-Path Forest., , , , and . ICASSP, page 2190-2193. IEEE, (2010)