Smooth voxel surface for medical volumetric rendering

Author(s):  
Porawat Visutsak ◽  
Fuangfar Pensiri ◽  
Orawan Chaowalit
Keyword(s):  
2009 ◽  
Author(s):  
Dennis H. Bunfield ◽  
Darian E. Trimble ◽  
Gary H. Ballard

2020 ◽  
Vol 6 (9) ◽  
pp. 88
Author(s):  
Porawat Visutsak

This paper aims to implement histogram pyramids with marching cubes method for 3D medical volumetric rendering. The histogram pyramids are used for feature extraction by segmenting the image into the hierarchical order like the pyramid shape. The histogram pyramids can decrease the number of sparse matrixes that will occur during voxel manipulation. The important feature of the histogram pyramids is the direction of segments in the image. Then this feature will be used for connecting pixels (2D) to form up voxel (3D) during marching cubes implementation. The proposed method is fast and easy to implement and it also produces a smooth result (compared to the traditional marching cubes technique). The experimental results show the time consuming for generating 3D model can be reduced by 15.59% in average. The paper also shows the comparison between the surface rendering using the traditional marching cubes and the marching cubes with histogram pyramids. Therefore, for the volumetric rendering such as 3D medical models and terrains where a large number of lookups in 3D grids are performed, this method is a particularly good choice for generating the smooth surface of 3D object.


2008 ◽  
Vol 139 (2_suppl) ◽  
pp. P103-P103
Author(s):  
Jen-Fang Yu ◽  
Wei-Chung Chin ◽  
Che-Ming Wu ◽  
Shu-Hang Ng

Problem To non-invasively measure in-vivo human inner ear by MRI and measure the geometry of vestibule by the reconstructed 3D model of inner ear for further diagnosis of large vestibular aqueduct syndrome (LVAS). Methods 3-T MR scanner, MAGNETOM Trio made by Siemens, was utilized. The TR/TE for MR imaging of 7 patients was 5.65/2.6 ms and the voxel size was 0.5 mm X 0.5 mm X 0.5 mm for single slice of 48 slices. The configuration of semicircular canals, vestibule and cochlea could be detected by threshold. The 3D geometry of inner ear was then computed based on the thickness of slice. Results The surface area and volume of semicircular canals for 7 normal ears were 217.85 square mm and 63.56 cubic mm; of vestibule were 105.88 square mm and 56.36 cubic mm; of cochlea were 171.84 square mm and 81.29 cubic mm respectively. The variation of volumes of vestibule and cochlea could be quantified non-invasively. The correlation between the volume and the level of LVAS will be analyzed once the number of volunteer reaches a statistically significant level. Conclusion The variation for the geometry of vestibule could be measured non-invasively. The grade of LVAS can be assessed by the obtained 3D model of semi-circular canal, vestibule and cochlea. Significance According to the 3D model, the geometry of inner ear can be measured, and the syndrome can be revealed directly to help clinical diagnosis of LVAS more accurately.


2012 ◽  
Vol 18 (10) ◽  
pp. 1731-1743 ◽  
Author(s):  
Insoo Woo ◽  
Ross Maciejewski ◽  
Kelly P. Gaither ◽  
David S. Ebert

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