Manuscript of: Marek Koci´ nski, Artur Klepaczko, Andrzej Materka, Martha Chekenya and Arvid Lundervold 3D image texture analysis of simulated and real-world vascular trees Published: Elsevier, Computer Methods and Programs in Biomedicine, Volume 107, Number 2, August 2012, Pages 140 − 154, ISSN 0169 − 2607 doi:10.1016/j.cmpb.2011.06.004 3D image texture analysis of simulated and real-world vascular trees M. Koci´ nski, A. Klepaczko, A. Materka, M. Chekenya, A. Lundervold Institute of Electronics, Technical University of  L´od´ z W´olcza´ nska 211/215, 90-924  L´od´ z, Poland marek.kocinski@p.lodz.pl Abstract A method is proposed for quantitative description of blood-vessel trees, which can be used for tree classification and/or physical param- eters indirect monitoring. The method is based on texture analysis of 3D images of the trees. Several types of trees were defined, with dis- tinct tree parameters (number of terminal branches, blood viscosity, input and output flow). A number of trees was computer-simulated for each type. 3D image was computed for each tree and its texture features were calculated. Best discriminating features were found and applied to 1-NN nearest neighbor classifier. It was demonstrated that (i) tree images can be correctly classified for realistic signal-to-noise ratio, (ii) some texture features are monotonously related to tree pa- rameters, (iii) 2D texture analysis is not sufficient to represent the trees in the discussed sense. Moreover, applicability of texture model to quantitative description of vascularity images was also supported by unsupervised exploratory analysis. Eventually, the experimental con- firmation was done, with the use of confocal microscopy images of rat brain vasculature. Several classes of brain tissue were clearly distin- guished based on 3D texture numerical parameters, including control and different kinds of tumour — treated with NG2 proteoglycan to promote angiogenesis-dependent growth ot the abnormal tissue. The 1