Preliminary Volumetric Calculation of the Mucosal Surface in the Nares of Lambs Using a Segmentation of Computed Tomographic Images

Intranasal vaccinations are becoming more important in both human and animal medicine to generate a localized IgA immune response not seen with parenteral vaccinations. This localized IgA response is more effective at reducing pathogen load on the mucosal surface of a potential host. One prerequisite for a successful nasal vaccination is the need to understand the distribution pattern of the nebulized vaccine, which requires an understanding the volume of the nares as well as the mucosal surface area. The exact mucosal surface area of ruminant nares has not yet been investigated. The aim of this concept study is to provide a detailed breakdown of a new method of volumetric rendering that can be used to calculate the volume and mucosal surface area of ruminant nares from computed tomographic images. The program Seg 3D was used to perform semi-automatic segmentation of a CT scan of a 9-month-old lamb head. Threshold segmentation and manual segmentation were used in combination to select the lamb's nasal cavity. The segmentation process yielded a volumetric rendering that was used to calculate the surface area and volume of the lamb's nasal cavity, with the segmentation process was repeated for each individual side of the lamb's nares. The surface area of the mucosal surface of each nostril is approximately 448 cm2, and the volume is approximately 45 cm3. The methodology described in this study successfully calculated the volume and surface area of a lamb's nares using volumetric rendering.

Marching Cubes and Histogram Pyramids for 3D Medical Visualization

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.

Marching Cubes and Histogram Pyramids for 3D Medical Visualization

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. This feature will be then 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 that 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.