The Artifacts Produced on the Images during CT Scans - Assignment Example

Thе Аrtifасts Рrоduсеd on the Images during СT Sсаns Name Professor Course Date Table of Contents Table of Contents 2 Figure 10.1: Simulation results from the Shepp-Logan head phantom Noise induced streak artifacts (St Lukes Orthopaedic Surgery Center, 2013…………………………………………………………………………………………...10 3 Fig. 7.3 A sample of Beam hardening streak artifacts (Oral and Maxillofacial Radiology University of Texas Health Science Center San Antonio, TX, 2012)…………………………….8 3 Introduction 3 A sample image of a CT scanner 4 Types of artifacts 5 Motion steak artifacts 5 Sample picture of a motion streak artifact 6 Metal streak artifacts 6 Beam hardening streak artifacts 7 Fig. 7.3 A sample of Beam hardening streak artifacts http://www.aadmrt.com/currents/lee_summer_08_print.htm 9 Noise induced streak artifacts 10 Figure 10.1: Simulation results from the Shepp-Logan head phantom -Noise induced streak artifacts http://ej.iop.org/images/0031-9155/57/22/7519/Full/pmb424674f2_online.jpg 11 Table of figures Figure 2.4. A sample image of a CT Scanner (John Hopkins Hospital, 2011)…………………..3 Fig 4.2. A Sample picture of a motion steak artifact (St Lukes Orthopaedic Surgery Center, 2013)…………………………………………………………………………................................5 Fig 6.2. A sample image of a metal streak artifact (John Hopkins Hospital, 2011)………………6 Figure 10.1: Simulation results from the Shepp-Logan head phantom Noise induced streak artifacts (St Lukes Orthopaedic Surgery Center, 2013…………………………………………………………………………………………...10 Fig. 7.3 A sample of Beam hardening streak artifacts (Oral and Maxillofacial Radiology University of Texas Health Science Center San Antonio, TX, 2012)…………………………….8 Fig. 8.3 A sample of partial volume streak artifacts (Oral and Maxillofacial Radiology University of Texas Health Science Center San Antonio, TX, 2012)…………………………..9 Idеntify thе аrtifасts рrоduсеd оn thе images during СТ sсаns. Dеsсribе thе mеthоds usеd tо rеduсе оr rеmоvе thеsе аrtifасts Introduction Computed tomography scan is one of the most current imaging procedures used in most healthcare institutions. This medical imaging procedure utilizes computer processed x-rays in image production. During its functionality, this scan can also take a slice of a specific body part and present its image (Zhang 2009, 140). The cross sectional images produced here are normally used for various function including therapeutic purposes. The computerized scanner uses digital geometry to generate three-dimensional images from the inside of an object with just a single round of rotation. A sample image of a CT scanner Figure 2.4. A sample image of a CT Scanner http://www.wired.com/gadgets/miscellaneous/news/2008/04/Toshiba_CTScanner The data produced by the CT scanner can be manipulated into various forms when demonstrating the ability of various body structures in blocking X-ray beam. Historically, the images that were initially produced by these scanners came as transverse planes; the most current ones allow the data produced to be formatted in various planes like the 3D images (Zhang 2009, 140). CT is not only used in medical institutions, but also in other disciplines like non-destructive material testing. Despite the rampant increase in CT scan usage, there are certain artifacts that are normally produced alongside the images. These tend to make the images difficult to read or translate. They can easily cause the images to acquire undesired shapes and qualities that in the end may lead to misinterpretation of the facts ((Eliada 2010, 139). The occurrence of this can lead to various risk factors, which are great hazards to both the patients and the radiographer. The aim of this study is to investigate the various artifacts produced on images during CT scans and the corresponding measures and procedures that can be put in place to ensure these are sufficiently controlled (Eliada 2010, 133). Types of artifacts Classification of artifacts can be done based on the appearances of the CT artifacts. The artifacts can be classified into various categories namely shadings, distortions, streaks, bands and rings. Scatter radiation are some of the causes of shading artifacts. The various types of artifacts include the following; metal artifacts, motion artifacts, noise induced artifacts, partial volume artifacts and beam hardening artifacts (Zhang 2009, 240). Motion steak artifacts This type of artifact comes because of motion during the capture of the image. As a result, the CT machine may create a distorted or rather a blurred image, which may be difficult to analyze. The greatest cause of such motions is the respiratory motion during the process of image acquisition (Tack 2012, 261). The third generation scanners have good scanning time, though if the patients do not make any motion at all, there is a risk of a large scan portion being affected due to the effect of multilayered acquisition of images hence poor quality in results. The resulting motions normally emerge as streaks on the images, which come about because of inability of the CT scanner to construct algorithm, which will work with the conflicted data. The scanner will thus find it hard to locate the voxel. Sample picture of a motion streak artifact Fig 4.2. These image shows the sample picture of a motion steak artifact http://abcradiology.blogspot.com/2011/11/computed-tomography-artifacts.html Immobilization of the patient during the scan is one of the ways of reducing movements. The immobilization should be voluntary and make the patient as comfortable as possible as well as stable. It is also prudent to make the patient aware of the dire consequences that a single motion can cause in the results (Warriner 2010, 150). Metal streak artifacts Metallic substances in the body can greatly interfere with the final scan results obtained. They create streaks during the scan process hence making the images blurred and unclear to read (Warriner 2010, 100). The presence of these substances in the body results into various artifacts during scan, hence causing streaks in the images produced. Sample image of metal streak artifact Fig 6.2. This is a sample image of a metal streak artifact http://radiology.rsna.org/content/263/3/696/F7.expansion.html Certain techniques have been known to significantly reduce the effects of these metallic substances on the scan results (Tack 2012, 130). One of such is the interactive reconstruction methods; this technique reconstructs the corrupted data and the metallic artifact on the image ignored. Algorithms use has also been proposed as reliable but most professionals claim it is noisy and quite expensive due to its high computational power. In the end, a new image is created which is a practical preview of what ought to be (Haimerl 2008, 100). Beam hardening streak artifacts This is the increase in the x-ray beam intensity while performing the scan on a patient. Due to increase in object size, the average beam energy gains a shift; since low energy photons get absorbed, the high-energy photons pass through the object. Consequently, the beam hardening artifacts can be witnessed when radiation beams take different paths (Haimerl 2008, 127). As a result, the beam numbers of certain structures change resulting into streaks and bands on the final image. To remove these beam hardening artifacts, a bowtie filter is used in the CT scan. The function of the bowtie filter is to create uniformity at the beam detector. This will control the creation of high-energy photons and low energy photons hence lowering the risk of streaks on the images produced (Haimerl 2008, 107). In addition, a beam hardening software can be used to correct the effects brought about by beam hardening. The software controls the beam size making the image appear in high quality. Fig. 7.3 A sample of Beam hardening streak artifacts http://www.aadmrt.com/currents/lee_summer_08_print.htm Partial volume streak artifacts The calculations on CT numbers are normally based on linear attenuation and coefficient for the voxel tissue. In cases where the voxel contain only a single tissue type, calculation of the CT numbers is always very simple (Eliada 2010, 109). Partial volume averaging normally occur when the voxel has trio similar tissue types that has closely compacted CT numbers e.g. blood =40, white matter = 46 and gray matter=43 (Eliada 2010, 135). This voxels CT number is got by finding the average of these three (43). The averaging of the CT numbers can result into partial volume artifacts hence lower the quality of images produced. In such instance, streaks and rings will appear. To correct the effects of the partial volume artifact ,measures such as computer algorithms and implementation of double offset planning be put in place (Forster and Marianne 2012, 84). These two techniques can significantly reduce the effects of partial volume artifacts and result into clear images without streaks and bands. In addition, adaptive filtration technique can be applied to control this artifact (Haimerl 2008, 150). This will lower the image intensity in the areas affected and vice versa causing uniformity in the final image. Fig. 8.3 A sample of partial volume streak artifacts http://www.appliedradiology.com/Issues/2003/08/Articles/Common-artifacts-in-computerized-tomography--A-review.aspx Noise induced streak artifacts Bad patient positioning during scan can lead to the striking of photons against the detectors hence causing noise (Haimerl 2008, 110). It is important to note that the noise induced streak artifacts occurs in CT as a result of the attraction of few photons owing to high attenuation along the lines in which the measurements are done. The photon noise is also believed to be caused by poor scan speed, it may be higher or lower depending on the CT scanner used. In addition, improper exposure could lead to this noise (Eliada 2010, 69). Every time the photons are reduced during scan, the noise increases hence resulting into streaks on the final image produced. It is noteworthy that the attempts to downsize these artifacts mainly lay emphasis on the use of adaptive filters so as to adjust it to local noise levels. The corrective measures that can be used include the use of algorithm techniques, ensuring proper positioning for patients, and ensuring sufficient exposure of the patient to the beam. Optimizing the CT scanner speed can also correct this menace. a b c d e f g Figure 10.1: Simulation results from the Shepp-Logan head phantom -Noise induced streak artifacts http://ej.iop.org/images/0031-9155/57/22/7519/Full/pmb424674f2_online.jpg Conclusion Many factors can lead to artifacts in CT images. Some of these may come voluntarily like in cases dealing with children or involuntarily during respiration (Eliada 2010, 130). Whether voluntary or involuntary, taking the best corrective measures can yield quality results. One of the best solutions to this problem is application of computational algorithm use during the scan to create a virtual image of what is needed. In addition, providing patients with stable and comfortable positions during the scan can greatly lower the risks of motion artifacts. More measures like the adaptive filtration models can be used to significantly control this (Haimerl 2008, 120). The use of new CT scanner models can help significantly in reducing this problem. They will ensure patients are stable during the scan process hence resulting into quality results. In addition, these new models engage the use of optimal parameters in patient examination. Applying these can help in ensuring high quality results as well as many health benefits to the patients (Eliada 2010, 190). Patients should also be informed of the scanning procedure and relevance of maintaining certain posture in it. References Forster, Michelle and Marianne Duffy. 2012. Having a CT scan: this leaflet explains what happens when you go to hospital for a CT scan. London: Elfrida Society. Haimerl, Martin. 2008. Microlocal processing of CT scan data: applications for metal artifact reduction. Karlsruhe: Univ., Europ. Inst. für Systemsicherheit. Eliada, Morrison. 2010. Inter-plane artifact suppression in tomosynthesis using 3D CT image data. New York: BioMed Central Ltd. Tack, Davies. 2012. Radiation dose from multidetector CT. 2nd ed. Berlin: Springer. Warriner, Davies. 2010. The impact of motion artifacts on the reproducibility of repeated coronary artery calcium measurements. Edinburgh: Springer. Zhang, Yan. 2009. Three-dimensional image quality evaluation and improvement in flat-panel detector based cone-beam CT imaging. Rochester, N.Y.: University of Rochester. Figures references Figure 2.4. A sample image of a CT Scanner (John Hopkins Hospital, 2011). Fig 4.2. These image shows the sample picture of a motion steak artifact (St Lukes Orthopaedic Surgery Center, 2013). Fig 6.2. This is a sample image of a metal streak artifact (John Hopkins Hospital, 2011) Figure 10.1: Simulation results from the Shepp-Logan head phantom Noise induced streak artifacts (St Lukes Orthopaedic Surgery Center, 2013). Fig. 7.3 A sample of Beam hardening streak artifacts (Oral and Maxillofacial Radiology University of Texas Health Science Center San Antonio, TX, 2012) Fig. 8.3 A sample of partial volume streak artifacts (Oral and Maxillofacial Radiology University of Texas Health Science Center San Antonio, TX, 2012). Read More