ISSN 2079-3537      

 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                                                                                             
Scientific Visualization
Issue Year: 2015
Quarter: 4
Volume: 7
Number: 4
Pages: 27 - 43
Article Name: 3D SCIENTIFIC VISUALIZATION AND GEOMETRIC MODELING IN DIGITAL BIOMEDICINE
Authors: V.E. Turlapov (Russian Federation), N.I. Gavrilov (Russian Federation)
The paper is recommended by program committee of 25th International Conference on Computer Graphics and Vision GraphiCon’2015.
Address: V.E. Turlapov
vadim.turlapov@gmail.com
Lobachevsky State University of Nizhni Novgorod, Russian Federation

N.I. Gavrilov
gavrilov86@gmail.com
Lobachevsky State University of Nizhni Novgorod, Russian Federation
Abstract: The purpose of this paper is to review the state-of-the-art of software for three-dimensional scientific visualization, segmentation, and geometric modeling, which serves the contemporary three-dimensional digital biomedicine. The three-dimensional digital medicine is a rapidly growing industry that requires the involvement of a growing number of professionals. The importance of the topic is due to the need of developing holistic view of the area, vision of actual problems, and approaches to their solution in the scientific community.
The arsenal of libraries, software packages, and systems, which can be used in solving the actual problems, is surveyed. The focus is on the libraries of scientific visualization and 3D medical imaging, segmentation as well as geometric modeling and reconstruction. New 3D medical technologies based on these and similar libraries are presented. The possibilities of open libraries, software packages and systems for scientific visualization and segmentation, such as VTK, ITK, CMake, ParaView (all four supported by Kitware Inc.), VisIt (supported by Lawrence Livermore National Laboratory), and ITK-SNAP as well as for geometric modeling, such as CGAL, Open CASCADE, and SALOME, are characterized.
Also open software packages for segmentation and reconstruction of the data of electron microscopy (EM), such as ILASTIK, or CellBlender, and for cell modeling - Monte Carlo Cell (the last two supported by MMBioS and around community), and special package VMTK for modeling the dynamics of blood flow in the cardiovascular system are considered.
The possibilities of an open and proprietary, world and Russian modern medical 3D visualization such as Fovia HDVR®, Inobitec, Multivox3d, InVols (UNN) are presented. The problem of quality of the 3D visualization, where it is never possible to have a reference image, and the solition of this problem by synthesizing a virtual reference image by averaging a series of images with a random ray start is discussed. Pre-integration stage and research of methods in the plane of the "performance-quality" axes are found absolutely necessary for high quality code.
The possibilities, trends and depth parameterization of modern models of the human anatomy from the world's leading companies Nhumi Technologies, Visible Body, Plasticboy store, Zygote Inc. are shown. Existing products and technologies of 3D reconstruction of the patient's body via the camera and software from BodyKIT Body Labs, Itseez3d from Itseez are mentioned. Opportunities and challenges of medical technology "virtual anatomical table" and the implementation of modern Anatomage Inc., Sectra and similar functions, but as cloud services via InVols, are reviewed.
In the conclusion, we discuss the problems of digital biomedicine not yet solved by the community as well as the ways to solve them. These problems include (i) segmentation and quantification of 3D abnormalities to automate diagnosis and (ii) personalization of the parameterized model of human anatomy by extracting parameters from a personal tomography. We outline an effective approach to solving these problems by combining segmentation algorithms with geometric reconstruction in the form of parameterized models.
The novelty lies in the systemic coverage of the theme, setting actual goals and recommendations for their effective solution.
Language: Russian


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