scholarly journals Improved Visualisation of Patient-Specific Heart Structure Using Three-Dimensional Printing Coupled with Image-Processing Techniques Inspired by Astrophysical Methods

2019 ◽  
Vol 9 (2) ◽  
pp. 267-273
Author(s):  
I. Brewis ◽  
J. A. Mclaughlin

The aim of this study is to use image-processing techniques developed in the field of astrophysics as inspiration for a novel approach to the three-dimensional (3D) imaging of periprocedural medical data, with the intention of providing improved visualisation of patient-specific heart structure and thereby allowing for an improved quality of procedural planning with regards to individualized cardiovascular healthcare. Using anonymized patient DICOM data for a cardiac computed tomography (CT) angiography, two-dimensional slices of the patient's heart were processed using a series of software packages in order to produce an accurate 3D representation of the patient's heart tissue as a computer-generated stereolithography (STL) file, followed by the creation of a tactile 3D printout. We find that the models produced provide clear definition of heart structure, in particular in the left atrium, left ventricle and aorta. This level of clarity also allows for the aortic valve to be observed and 3D printed. This study provides a step-by-step blueprint of how this can be achieved using open source software, specifically Slicer 4.8.1, MeshLab and AutoDesk Netfabb. In addition, the implementation of astrophysical image-processing techniques shows an improvement in modelling of the heart based on the CT data, in particular in the case of small-scale features where echocardiography has previously been required for more reliable results.

Author(s):  
B.V.V. Prasad ◽  
E. Marietta ◽  
J.W. Burns ◽  
M.K. Estes ◽  
W. Chiu

Rotaviruses are spherical, double-shelled particles. They have been identified as a major cause of infantile gastroenteritis worldwide. In our earlier studies we determined the three-dimensional structures of double-and single-shelled simian rotavirus embedded in vitreous ice using electron cryomicroscopy and image processing techniques to a resolution of 40Å. A distinctive feature of the rotavirus structure is the presence of 132 large channels spanning across both the shells at all 5- and 6-coordinated positions of a T=13ℓ icosahedral lattice. The outer shell has 60 spikes emanating from its relatively smooth surface. The inner shell, in contrast, exhibits a bristly surface made of 260 morphological units at all local and strict 3-fold axes (Fig.l).The outer shell of rotavirus is made up of two proteins, VP4 and VP7. VP7, a glycoprotein and a neutralization antigen, is the major component. VP4 has been implicated in several important functions such as cell penetration, hemagglutination, neutralization and virulence. From our earlier studies we had proposed that the spikes correspond to VP4 and the rest of the surface is composed of VP7. Our recent structural studies, using the same techniques, with monoclonal antibodies specific to VP4 have established that surface spikes are made up of VP4.


2003 ◽  
Vol 26 (1) ◽  
pp. 10127 ◽  
Author(s):  
L David Suits ◽  
TC Sheahan ◽  
P Gachet ◽  
G Klubertanz ◽  
L Vulliet ◽  
...  

2009 ◽  
Vol 09 (03) ◽  
pp. 389-410 ◽  
Author(s):  
CHANDRIKA KAMATH ◽  
ABEL GEZAHEGNE ◽  
PAUL MILLER

The use of high-performance computers in computer simulations of physical phenomena has resulted in the generation of massive amounts of data. The analysis of these data can be challenging given their size and the complexity of the structures observed. In this paper, we describe how we can use image processing techniques to identify and count coherent structures in three-dimensional simulations of the Rayleigh-Taylor instability, which occurs when one fluid is being accelerated by a second fluid. As the two fluids mix, coherent structures are formed which grow, shrink, change shape, split, and merge with time. We describe the challenges faced in the analysis and show how we can combine image processing techniques with problem-specific characteristics to successfully analyze terabyte-sized data sets.


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