Computed Tomography Equipment Techniques PDF

‫جامعة العين‬ ‫كلية التقنيات الصحية والطبية‬ ‫قسم تقنيات االشعة والسونار‬ C o m p u t e d Tomography E q u i p m e n t Te c h n i q u e s Interpolation Algorithms and Pitch Dr. Hussein A.Dakhild Ph.D. Medical Imag...

‫جامعة العين‬ ‫كلية التقنيات الصحية والطبية‬ ‫قسم تقنيات االشعة والسونار‬ C o m p u t e d Tomography E q u i p m e n t Te c h n i q u e s Interpolation Algorithms and Pitch Dr. Hussein A.Dakhild Ph.D. Medical Imaging Technology  I n te r p o l ati o n A lg o r i th m s Reconstruction of an image at any z-axis position is possible because of a mathematical process called interpolation. the Figure below presents a graphic representation of interpolation and extrapolation. If one wishes to estimate a value between known values, that is an interpolation; if one wishes to estimate a value beyond the range of known values, that is an extrapolation. During helical CT, image data are received continuously, as shown by the data points in Figure A. When an image is reconstructed, as in Figure B, the plane of the image does not contain enough data for reconstruction. The data in that plane must be estimated by interpolation. Data interpolation is performed by a special computer program called an interpolation algorithm. Image interpolation creates a number of new slices between known slices in order to obtain an isotropic volume image. The problem with continuous tube and table motion was that projections precessed in a helical motion around the patient and did not lie in a single plane. This meant that conventional reconstruction algorithms could not work. Helical CT scanning produces a data set in which the x-ray source has travelled in helical trajectory around the patient, (the data are acquired in a helical path around the patient). Present day CT reconstruction algorithms assume that the x- ray source has negotiated a circular not a helical path around the patient. To compensate for these differences in the acquisition geometry, before the actual CT reconstruction the helical data set is interpolated into a series of planar image data sets (the reconstruction plane of interest). Interpolation is essentially a weighted average of the data from either side of the reconstruction plane, with slightly different weighting factors used for each projection angle. In summary: Interpolation Algorithms are the mathematical process required to reconstruct axial images from the spiral volume data set.  P i tch During helical scans, the table motion causes displacement of the fan beam projections along the z axis; the relative displacement is a function of the table speed and the beam width. The ratio of table displacement per 360° rotation to section thickness is termed pitch. Pitch is the table travel per rotation divided by beam width. (pitch = table travel / beam width) o pitch = 1 - coils of the helix are in contact o pitch < 1 - coils of the helix overlap o pitch > 1 - coils of the helix are separated  example If beam width is 10cm, the table moves 10cm during one tube rotation, then pitch is 1, so, x-ray beam associated with consecutive helical loops are contiguous. If beam width is 10cm and table moves 15cm per tube rotation, then pitch is 1.5 So, a gap exists between the x-ray beam edge of consecutive loop. If beam width is 10cm and table moves 7.5cm then pitch is 0.75, so, beams and consecutive loops overlap by 2.5 (doubly irradiating the underlying tissues).  Volume imaging Volume Imaging CT (Computed Tomography) is an advanced imaging technique that captures a large volume of data in a single, continuous scan, often in a 3D format. Traditional CT scans create cross-sectional (2D) images, but volume imaging CT collects data over a larger area, allowing for 3D reconstructions of the scanned region. This makes it possible to view organs, tissues, or other structures from multiple angles with high accuracy and detail. The relationship between the volume of tissue imaged and pitch is given as follows: helical CT scanner Advantages  Fast scan times and large volume of data collected.  Minimizes motion artifacts.  Less mis-registration between consecutive slices.  Reduced patient dose.  Improved spatial resolution.  Enhanced multiplaner or 3D renderings.  Improved temporal resolution