Optimization of the process of creating models of human blood vessels

Bibliography:
1 Trushel NA, Mansurov VA. Mathematical modeling of blood fow in the area of branching of the internal carotid artery into fnite branches. In: Morphology — science and practical medicine: collection of scientifc works dedicated to the 100th anniversary of Vitebsk State Medical University n. a. N. N. Burdenko. Vitebsk, 2018; p. 377–83
2 Fomkina OA, Ivanov DV, Kirillova IV, Nikolenko VN. Biomechanical modelling of cerebral arteries at diferent variants of confguration of intracranial arteries of vertebrobasilar system. Saratov Journal of Medical Scientifc Research 2016; 12 (2): 118–27
3 Fomkina OA. Regularities of individual typological variability of morphometric and biomechanical parameters of cerebral arteries: DSc diss. Saratov, 2017; 240 p.
4 Ivanov D, Dol A, Pavlova O, Aristambekova A. Modeling of human circle of Willis with and without aneurisms. Acta Bioeng Biomech 2014; 16 (2): 121–9
5 Shao H, Qin H, Hou Y, et al. Reconstructing 3D Model of Carotid Artery with Mimics and Magics. Advances in Information Technology and Education 2011; 201: 428–33
6 Drapikowski P, Domagala Z. Semi-automatic segmentation of CT / MRI images based on active contour method for 3d reconstruction of abdominal aortic aneurysms. Image Processing & Communication 2014; 19 (1): 13–20
7 Fresno M, Venere M, Clausse A. A combined region growing and deformable model method for extraction of closed surfaces in 3D CT and MRI scans. Computerized Medical Imaging and Graphics 2009; 33: 369–76
8 Matveenko VP, Shardakov IN, Shestakov AP. Algorithm for creating three-dimensional images of human organs from tomographic data. Russian Journal of Biomechanics 2011; 15 (4): 20–32
9 Jermyn M, Ghadyani H, Mastanduno MA, et al. Fast segmentation and high-quality three-dimensional volume mesh creation from medical images for difuse optical tomography. J Biomed Opt 2013; 18 (8): 86007
10 Fedorov A, Beichel R, Kalpathy-Cramer J, et al. 3D Slicer as an Image Computing Platform for the Quantitative Imaging Network. Magnetic Resonance Imaging 2012; 30: 1323– 41
11 Antiga L, Piccinelli M, Botti L, et al. An image-based modeling framework for patient-specifc computational hemodynamics. Med Biol EngComput 2008; 46 (11): 1097–112
12 Yushkevich PA, Piven J, Hazlett HC, et al. User-guided 3D active contour segmentation of anatomical structures: Signifcantly improved efciency and reliability. NeuroImage 2006; 31: 1116–28
13 Cao J, Wu X. A novel level set method for image segmentation by combining local and global information. Journal of Modern Optics 2017; 64 (21): 2399–412
14 Bidgood WD, Horii SC, Prior FW, Van Syckle DE. Understanding and Using DICOM, the Data Interchange Standard for Biomedical Imaging. J Am Med Inform Assoc 1997; 4 (3) 199–212
15 Suh BY, Yun WS, Kwun WH. Carotid artery revascularization in patients with concomitant carotid artery stenosis and asymptomatic unruptured intracranial artery aneurysm. Ann Vasc Surg 2011; 25 (5): 651–5
16 Heman LM, Jongen LM, Van Der Worp HB, et al. Incidental intracranial aneurysms in patients with internal carotid artery stenosis. Stroke 2009; 40 (4): 1341–6
17 Radak D, Sotirovic V, Tanaskovic S, Isenovic ER. Intracranial aneurysms in patients with carotid disease: not so rare as we think. Angiology 2014; 65 (1): 12–6
18 Kudashev AL, Hominets VV, Tereshonok AV, et al. Biomechanical background of the formation of the transitional proximal kyphosis after pedicle fxation of the lumbar spine. Russian Journal of Biomechanics 2017; 21 (3): 313–23
19 Kudashev AL, Hominets VV, Tereshonok AV, et al. Biomechanical modeling in surgical treatment of a patient with a true spondylolisthesis of the lumbar vertebra. Spine surgery 2018; 15 (4): 87–94.