{'fraction_non_alphanumeric': 0.0239067055393586, 'fraction_numerical': 0.004081632653061225, 'mean_word_length': 5.085106382978723, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
MODELING INTRAORGAN VASCULATURE USING PROCEDURAL AND MATHEMATICAL SPACE TRANSFORMATIONS

Background. The electronic methods in medicine are getting more widespread. The COVID-19 pandemic forced remote IT technologies to develop. It is necessary to create medical e-learning systems, in particular, to study anatomy of human organ vasculatures. 
Purpose. To create universal and realistic 3d-model of intraorgan vasculatures based on the vasculature morphometry results. 
Materials and methods. Morphometric data of real vascular networks, geometric modeling in plane and in scape, procedural spatial transformation of the vasculature according to the law of a logarithmic spiral were used. 
Results. A two-staged sequence for construction a geometric 3d-model is proposed. The model is built of the units of vasculature, which are called bifurcations (dichotomies). At the first stage, mathematical 2d-model of a vascular network fragment is build based on morphometric data of the geometry of vasculature. It reflects the structure and quantitative characteristics of the vascular bifurcations (dichotomies). At the second stage, data about third special coordinate is added and a procedural 3d-model of the fragment is built. To increase the accuracy of the model, the ability to bend the vessels and to differ diameters of their starting and ending points have been added. 
Conclusion. The universal 3d-model of a tree-like structure is presented as a visualization of the intraorgan vasculature. These models can be used as visual teaching aids in online education environment. To increase the informative and educational value of the model, visual images of various pathologies of the vasculature can be added.