CT Imaging and Reconstruction Quiz

Computed Tomography (CT)

• CT is a medical imaging technique
• CT images are developed from multiple X-ray absorption measurements
• CT images show thin slices of the body
• CT image formation is a three-step process:
  • Scan (or Data Acquisition): X-ray tube scans the patient systematically, collecting sufficient data for reconstruction. The sum of X-ray transmission through each detector yields a projection. Multiple projections are taken at various angles.
  • Image Reconstruction: Using complex computer algorithms, mathematical equations, and physics, raw data is processed to generate a slice image.
  • Image Display: Electrical signals from the image reconstruction are converted into a visual image on a monitor. Different shades of gray represent different CT numbers.

CT Image Formation: Geometries

• Two projection geometries are used in CT imaging:
  • Parallel beam geometry: X-rays travel parallel to one another.
  • Fan beam geometry: In this geometry, X-rays diverge from a source point at varying angles in a fan-like pattern.
  • Cone beam geometry

Image Reconstruction

• The process uses raw data to create an image.
• The process uses complex computer algorithms, mathematical equations, and physics
• When the source-detector makes a sweep across the patient, X-ray beam attenuation varies based on tissue density and effective atomic number (Z), producing projections
• The intensity profile or projection is calculated; the values are stored digitally
• The computer processes projections to reconstruct an image of the anatomical structure.
• The individual values of the matrix elements are obtained by solving simultaneous equations.
• The matrix represents cross-sectional anatomy.
• Dedicated array processors are used for fast calculations and display.
• Common algorithms in image reconstruction include iterative techniques, back projection, and filtered back projection.

Image Reconstruction: Types

• Prospective reconstruction: Image generation during the scan
• Retrospective reconstruction: Data from previous scans analyzed to create a new image

Image Display

• Image display components convert digital data into electrical signals for the CT monitor.
• Images are displayed on a cathode ray tube (CRT) or flat-panel displays (e.g., TFT LCD)
• Each CT number is assigned a shade of gray (typically 256 shades).

Image Reformation (Post-Processing)

• Image post-processing technique for CT
• Raw Data: Initial measurements (projections) from the CT scanner during patient scan.
• Image Data: Processed, reconstructed form of raw data from applying mathematical transformations.
• DFOV (zoom/target): determines the portion of raw data used to create the image.

Image Reformation: Parameters

• Field of view (FOV): Geometric midpoint of the reconstructed CT image.
• Anisotropic voxel: Voxels with unequal dimensions (often with thinner slices in one dimension).
• Isotropic voxel: Voxels with equal dimensions in all three axes (x, y, z). Facilitates 3D reconstructions.

CT Image Reformatting Techniques

• Two-dimensional formats: Multiplanar reformation (MPR), Curved planar reformation (CPR)
• Three-dimensional formats: Surface shaded displays (SSD), Volume rendering (VR), Average intensity projection (AIP), Maximum intensity projection (MIP), Minimum intensity projection (MinIP), Endoluminal imaging.

Multiplanar Reformation (MPR)

• Reformats anatomical structures; generates multiplanar images from axial scans
• Ideal for 2D viewing of anatomy.
• Produces coronal, sagittal, and paraxial views from axial data.
• Using isotropic voxel, produces virtually identical image quality to original axial images.
• Anisotropic voxels can be improved with overlapping images.

Curved Planar Reformation(CPR)

• Reformats anatomical data along the centerline of tubular structures, including vessels.
• Used for visualizing tubular structures effectively.

Intensity Projection Rendering

• Thin-slice algorithms like AIP, MIP, and MinIP are used in this technique.

Average Intensity Projection (AIP)

• Combines average attenuation values within voxels
• Useful for structures with low contrast, such as a solid body or walls of hollow structures (blood vessels/intestines).

Maximum Intensity Projection (MIP)

• Shows only the highest attenuation values within voxels
• Enables detection of high-intensity structures
• Used in angiographic and urographic images
• Limited view of 3D relationships in a volume.

Minimum Intensity Projection (MinIP)

• Shows only lowest attenuation values
• Identifies low-density structures (e.g., air-containing structures)
• Aids in diagnosing diseases, like bronchiectasis and emphysema.

Test your knowledge on computed tomography (CT) imaging and reconstruction algorithms. This quiz covers various aspects of image formation, data acquisition, and display processes in CT imaging. Answer questions about key concepts like DFOV, voxel characteristics, and reformatting techniques.