Intraoral, Panoramic, and CBCT Image Quality- Viewing 2D and 3D Images

brightness and contrast

-digital radiographs do not always use the full range of available gray values effectively

-can be relatively dark or light, showing too much contrast in certain areas or not enough

-digital imaging software commonly includes tools for the adjustment of brightness and contrast

histogram stretch and slide

-although the brightness and contrast can be judged visually, the image histogram is a convenient tool to examine which of the available gray values the image uses

-open the image that you want to work on and click at arrow

histogram stretch and slide step 2

-tool allows you to adjust the spectrum shown in the image

moving tool R/L

-move to the R: image changes darker because you use a smaller spectrum of color

-move to the L: image changes lighter

brightness and contrast

-2 ways to change brightness and contrast:

1) move mouse from R to L and up to down across the image to adjust parameters

2) using the box- can move small red circle in the box to adjust brightness and contrast

brightness and contrast box

-play with the box to see what would be changed

-move the mouse L and R to adjust brightness

-move mouse up and down to adjust contrast

sharpen/edge enhance

-purpose is to improve image quality by removing blur or noise

-can change sharpness from 1 to 10

magnification

-place the magnifier on the image to zoom the area of interest with a left click

-do NOT save modification in MiPACS

-need to save the original images

remember the 3 elements that will give us a radiographic image of diagnostic quality

standard CT orthogonal views

CBCT format data

-3 basic format options: multiplanar reformation, ray sum, volumetric rendering

multiplanar reformation (MPR)

-axial and panoramic images are used as reference images to show the location of the cross-sectional images

-cross-sectional images demonstrate the amount of undercut and location of the inferior alveolar canal

-can draw a panoramic curve or be as creative as we like for the clinic scenario

-draw different planes in any direction through the site of interest & image quality is not degraded because of these isotropic voxels

ray sum image

-not an actual 3D reconstruction

-get this image by finding a slice you like and pressing the ray sum function in the CBCT software

-software takes all the voxels within a selected thickness of the slice you like and adds them together (sums them) to give a thick slab of the image

-all the voxels represent air, bone, and soft tissues

panoramic ray sum

maximum intensity projection (MIP)

-method produces a “pseudo” 3D image by evaluating each voxel value along an imaginary projection ray from the observer’s eyes within the data set and then representing only the highest value as the display value

-projection ray identified throughout the entire volumetric data set, along which individual voxels are identified, each with varying grayscale intensity corresponding to various tissue densities

-MIP algorithm selects only those values along the projection ray with the highest values (usually corresponding to bone)

-represents only one pixel on the resultant image

MIP in practice

-not used often

MIP in practice- fracture

-might be helpful to visualize fractures prior to the surgery

manual segmentation

theory of manual segmentation

-often accomplished by an adjustable scale determining the upper and lower limits and range of intensity values to include in the segmentation

-visual result of changes in this scale is displayed in “real-time” to visualize the effects of incremental changes

-segmentation may be optimized to reveal the objects of interest including A) bone as a solid surface or shaded surface display, B) bone and the dentition under the bone as a transparency using volumetric imaging, C) bone, the dentition, and the soft tissue surface using volumetric imaging