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KONİK IŞINLI BİLGİSAYARLI TOMOGRAFİDE HAREKET VE GÜRÜLTÜ ARTEFAKTLARINDA PHOTOSHOP PROGRAMI KULLANIMI

Year 2021, Volume: 8 Issue: 2, 359 - 366, 31.08.2021
https://doi.org/10.15311/selcukdentj.649079

Abstract

Amaç: Baş
ve boyun bölgesinde konik ışınlı tomografi uygulamaları esnasında hareket ve
gürültü artefaktı oluşumu oldukça yaygındır. Altta yatan nedenler arasında
cihazın uzun çekim süresi, hastaların genel sağlığı nedeniyle kontrolsüz
hareketler ve çocuklar gibi hastaların aşırı hareketliliği vardır. Bu
çalışmada, Photoshop programını kullanarak artefaktları kaldırmak için çeşitli
filtre yöntemleri ve yazılım özellikleri incelenecektir.

Gereç ve Yöntemler:Gürültü ve hareket artefaktı bulunan beş farklı imaj seçildi. Bu seçim
sonrasında Photoshop filtreleri ile belirli yollar izledi. Programda işlenen ve
düzeltilen görüntüler uzman diş hekimleri tarafından değerlendirildi. Görüntü
değerlendirmelerinde filtrelemeden önce ve sonra, uzmanlar tarafından 1 ila 5
puan arasında olmak üzere değerlendirmeler yapıldı. Her imaj 1 çok yetersiz, 2
yetersiz, 3 normal, 4 yeterli, 5 çok iyi olarak skorlandı.

Bulgular: : 1 ile 5 arasında değerlendirilen 50 adet gürültü artefaktlı imajın
değerlendirilmesi sonucunda, ortalama puan 4.12, hareketli artefaktı bulunan
imajlar için ise 1.62'dir. Wilcoxon testinin sonuçlarına göre, hareket
artefaktı ve gürültü artefaktı ile kesitlerin postoperatif düzeltme oranı
arasında istatistiksel olarak anlamlı bir fark bulundu.

Sonuçlar: Konik ışınlı bilgisayarlı tomografi uygulamalarında birçok nedenden
ötürü oluşabilecek hareket artefaktı ve gürültü artefaktı ile sıkça
karşılaşılmaktadır. Bu gibi durumlarda, Photoshop programında ortaya çıkan
artefaktlar tersine çevrilebilir ve görüntüler tanısal açıdan
değerlendirilebilir.

Anahtar Kelimeler: konik ışınlı
bilgisayarlı tomografi, artefakt, gürültü, photoshop

References

  • 1. De Vos W, Casselman J, Swennen GR. Cone-beam computerized tomography (CBCT) imaging of the oral and maxillofacial region: a systematic review of the literature. International journal of oral and maxillofacial surgery. 2009;38(6):609-25.
  • 2. Kiljunen T, Kaasalainen T, Suomalainen A, Kortesniemi M. Dental cone beam CT: A review. Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics. 2015;31(8):844-60.
  • 3. Spin-Neto R, Costa C, Salgado DM, Zambrana NR, Gotfredsen E, Wenzel A. Patient movement characteristics and the impact on CBCT image quality and interpretability. Dento maxillo facial radiology. 2018;47(1):20170216.
  • 4. Spin-Neto R, Mudrak J, Matzen LH, Christensen J, Gotfredsen E, Wenzel A. Cone beam CT image artefacts related to head motion simulated by a robot skull: visual characteristics and impact on image quality. Dento maxillo facial radiology. 2013;42(2):32310645.
  • 5. Spin-Neto R, Wenzel A. Patient movement and motion artefacts in cone beam computed tomography of the dentomaxillofacial region: a systematic literature review. Oral surgery, oral medicine, oral pathology and oral radiology. 2016;121(4):425-33.
  • 6. Dach E, Bergauer B, Seidel A, von Wilmowsky C, Adler W, Lell M, et al. Impact of voxel size and scan time on the accuracy of three-dimensional radiological imaging data from cone-beam computed tomography. Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery. 2018;46(12):2190-6.
  • 7. Ouadah S, Jacobson M, Stayman JW, Ehtiati T, Weiss C, Siewerdsen JH. Correction of patient motion in cone-beam CT using 3D-2D registration. Physics in medicine and biology. 2017;62(23):8813-31.
  • 8. Sisniega A, Stayman JW, Yorkston J, Siewerdsen JH, Zbijewski W. Motion compensation in extremity cone-beam CT using a penalized image sharpness criterion. Physics in medicine and biology. 2017;62(9):3712-34.
  • 9. Yildizer Keris E. Effect of patient anxiety on image motion artefacts in CBCT. BMC oral health. 2017;17(1):73.
  • 10. Diaz-Flores-Garcia V, Labajo-Gonzalez E, Santiago-Saez A, Perea-Perez B. Detecting the manipulation of digital clinical records in dental practice. Radiography. 2017;23(4):e103-e7.
  • 11. Spin-Neto R, Matzen LH, Schropp LW, Sorensen TS, Wenzel A. An ex vivo study of automated motion artefact correction and the impact on cone beam CT image quality and interpretability. Dento maxillo facial radiology. 2018;47(5):20180013.
  • 12. Yang FQ, Zhang DH, Huang KD, Yang YF, Liao JM. Image artifacts and noise reduction algorithm for cone-beam computed tomography with low-signal projections. Journal of X-ray science and technology. 2018;26(2):227-40.
  • 13. Zhang H, Ouyang L, Ma J, Huang J, Chen W, Wang J. Noise correlation in CBCT projection data and its application for noise reduction in low-dose CBCT. Medical physics. 2014;41(3):031906.
  • 14. Ghazouani K, Ellouze N, Moussa IM. Comparative analysis between a variational method and wavelet method PURE-LET to remove poisson noise corrupting CT images. International Journal of Open Information Technologies. 2018;6(1).
  • 15. Liu Y, Gui Z, Zhang Q. Noise reduction for low-dose X-ray CT based on fuzzy logical in stationary wavelet domain. Optik - International Journal for Light and Electron Optics. 2013;124(18):3348-52.
  • 16. Zhang H, Liu Y, Han H, Wang J, Ma J, Li L, et al., editors. A comparison study of sinogram-and image-domain penalized re-weighted least-squares approaches to noise reduction for low-dose cone-beam CT. Medical Imaging 2013: Physics of Medical Imaging; 2013: International Society for Optics and Photonics.
  • 17. Tang X, Yang Y, Tang S. Characterization of imaging performance in differential phase contrast CT compared with the conventional CT--noise power spectrum NPS(k). Medical physics. 2011;38(7):4386-95.
  • 18. Hanzelka T, Foltan R, Horka E, Sedy J. Reduction of the negative influence of patient motion on quality of CBCT scan. Medical hypotheses. 2010;75(6):610-2.
  • 19. Zhang Q, Hu YC, Liu F, Goodman K, Rosenzweig KE, Mageras GS. Correction of motion artifacts in cone-beam CT using a patient-specific respiratory motion model. Medical physics. 2010;37(6):2901-9.
  • 20. Schulze R, Heil U, Gross D, Bruellmann DD, Dranischnikow E, Schwanecke U, et al. Artefacts in CBCT: a review. Dento maxillo facial radiology. 2011;40(5):265-73.
  • 21. Harris-Love MO, Seamon BA, Teixeira C, Ismail C. Ultrasound estimates of muscle quality in older adults: reliability and comparison of Photoshop and ImageJ for the grayscale analysis of muscle echogenicity. PeerJ. 2016;4:e1721.
  • 22. Kiranantawat K, Nguyen AH. Asian Rhinoplasty: Preoperative Simulation and Planning Using Adobe Photoshop. Seminars in plastic surgery. 2015;29(4):232-46.
  • 23. McLaren EA, Garber DA, Figueira J. The Photoshop Smile Design technique (part 1): digital dental photography. Compendium of continuing education in dentistry (Jamesburg, NJ : 1995). 2013;34(10):772, 4, 6 passim.
  • 24. McLaren EA, Goldstein RE. The Photoshop Smile Design Technique. Compendium of continuing education in dentistry (Jamesburg, NJ : 1995). 2018;39(5):e17-e20.
  • 25. Stieber JC, Nelson T, Huebner CE. Considerations for use of dental photography and electronic media in dental education and clinical practice. Journal of dental education. 2015;79(4):432-8.
  • 26. Wander P. Dental photography in record keeping and litigation. British dental journal. 2014;216(4):207-8.

Using Photoshop Program in Reducing Motion and Noise Artifacts On Cone Beam Ct

Year 2021, Volume: 8 Issue: 2, 359 - 366, 31.08.2021
https://doi.org/10.15311/selcukdentj.649079

Abstract

Background: Patient movement and noise artifacts are quite common during the CBCT exposure in the head and neck region. Among the underlying causes are the long duration of the device, uncontrolled movements due to the general health of the patients, and excessive mobility of the patients such as children. In this study, various filter methods and software features will be examined to remove artifacts by using Photoshop program.
Methods: Five different images with noise and motion artifact were selected. These sections were followed by specific paths with Photoshop filters. Images collected and corrected in the program were evaluated by specialist dentists. Before and after the filtering in the image evaluations, 1 to 5 criterions were evaluated by the experts. Each section was scored as 1 very inadequate, 2 inadequate, 3 normal, 4 adequate, 5 very good.
Results: As a result of the evaluation of 50 pieces of noise artifacts evaluated between 1 and 5, the average score was 4.12 points and the results were 1.62 for motion artifacts. According to the results of the Wilcoxon test, a statistically significant difference was found between the rate of postoperative correction of the sections with motion artifact and noise artifact.
Conclusion: Motion artifact and noise artifact which may occur due to many reasons are frequently encountered in CBCT examinations. In such cases, with the Photoshop program, the resulting artifacts can be reversed and can be evaluated from diagnostic point of view.
KEYWORDS
CBCT, Artifact, Noise, Photoshop

References

  • 1. De Vos W, Casselman J, Swennen GR. Cone-beam computerized tomography (CBCT) imaging of the oral and maxillofacial region: a systematic review of the literature. International journal of oral and maxillofacial surgery. 2009;38(6):609-25.
  • 2. Kiljunen T, Kaasalainen T, Suomalainen A, Kortesniemi M. Dental cone beam CT: A review. Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics. 2015;31(8):844-60.
  • 3. Spin-Neto R, Costa C, Salgado DM, Zambrana NR, Gotfredsen E, Wenzel A. Patient movement characteristics and the impact on CBCT image quality and interpretability. Dento maxillo facial radiology. 2018;47(1):20170216.
  • 4. Spin-Neto R, Mudrak J, Matzen LH, Christensen J, Gotfredsen E, Wenzel A. Cone beam CT image artefacts related to head motion simulated by a robot skull: visual characteristics and impact on image quality. Dento maxillo facial radiology. 2013;42(2):32310645.
  • 5. Spin-Neto R, Wenzel A. Patient movement and motion artefacts in cone beam computed tomography of the dentomaxillofacial region: a systematic literature review. Oral surgery, oral medicine, oral pathology and oral radiology. 2016;121(4):425-33.
  • 6. Dach E, Bergauer B, Seidel A, von Wilmowsky C, Adler W, Lell M, et al. Impact of voxel size and scan time on the accuracy of three-dimensional radiological imaging data from cone-beam computed tomography. Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery. 2018;46(12):2190-6.
  • 7. Ouadah S, Jacobson M, Stayman JW, Ehtiati T, Weiss C, Siewerdsen JH. Correction of patient motion in cone-beam CT using 3D-2D registration. Physics in medicine and biology. 2017;62(23):8813-31.
  • 8. Sisniega A, Stayman JW, Yorkston J, Siewerdsen JH, Zbijewski W. Motion compensation in extremity cone-beam CT using a penalized image sharpness criterion. Physics in medicine and biology. 2017;62(9):3712-34.
  • 9. Yildizer Keris E. Effect of patient anxiety on image motion artefacts in CBCT. BMC oral health. 2017;17(1):73.
  • 10. Diaz-Flores-Garcia V, Labajo-Gonzalez E, Santiago-Saez A, Perea-Perez B. Detecting the manipulation of digital clinical records in dental practice. Radiography. 2017;23(4):e103-e7.
  • 11. Spin-Neto R, Matzen LH, Schropp LW, Sorensen TS, Wenzel A. An ex vivo study of automated motion artefact correction and the impact on cone beam CT image quality and interpretability. Dento maxillo facial radiology. 2018;47(5):20180013.
  • 12. Yang FQ, Zhang DH, Huang KD, Yang YF, Liao JM. Image artifacts and noise reduction algorithm for cone-beam computed tomography with low-signal projections. Journal of X-ray science and technology. 2018;26(2):227-40.
  • 13. Zhang H, Ouyang L, Ma J, Huang J, Chen W, Wang J. Noise correlation in CBCT projection data and its application for noise reduction in low-dose CBCT. Medical physics. 2014;41(3):031906.
  • 14. Ghazouani K, Ellouze N, Moussa IM. Comparative analysis between a variational method and wavelet method PURE-LET to remove poisson noise corrupting CT images. International Journal of Open Information Technologies. 2018;6(1).
  • 15. Liu Y, Gui Z, Zhang Q. Noise reduction for low-dose X-ray CT based on fuzzy logical in stationary wavelet domain. Optik - International Journal for Light and Electron Optics. 2013;124(18):3348-52.
  • 16. Zhang H, Liu Y, Han H, Wang J, Ma J, Li L, et al., editors. A comparison study of sinogram-and image-domain penalized re-weighted least-squares approaches to noise reduction for low-dose cone-beam CT. Medical Imaging 2013: Physics of Medical Imaging; 2013: International Society for Optics and Photonics.
  • 17. Tang X, Yang Y, Tang S. Characterization of imaging performance in differential phase contrast CT compared with the conventional CT--noise power spectrum NPS(k). Medical physics. 2011;38(7):4386-95.
  • 18. Hanzelka T, Foltan R, Horka E, Sedy J. Reduction of the negative influence of patient motion on quality of CBCT scan. Medical hypotheses. 2010;75(6):610-2.
  • 19. Zhang Q, Hu YC, Liu F, Goodman K, Rosenzweig KE, Mageras GS. Correction of motion artifacts in cone-beam CT using a patient-specific respiratory motion model. Medical physics. 2010;37(6):2901-9.
  • 20. Schulze R, Heil U, Gross D, Bruellmann DD, Dranischnikow E, Schwanecke U, et al. Artefacts in CBCT: a review. Dento maxillo facial radiology. 2011;40(5):265-73.
  • 21. Harris-Love MO, Seamon BA, Teixeira C, Ismail C. Ultrasound estimates of muscle quality in older adults: reliability and comparison of Photoshop and ImageJ for the grayscale analysis of muscle echogenicity. PeerJ. 2016;4:e1721.
  • 22. Kiranantawat K, Nguyen AH. Asian Rhinoplasty: Preoperative Simulation and Planning Using Adobe Photoshop. Seminars in plastic surgery. 2015;29(4):232-46.
  • 23. McLaren EA, Garber DA, Figueira J. The Photoshop Smile Design technique (part 1): digital dental photography. Compendium of continuing education in dentistry (Jamesburg, NJ : 1995). 2013;34(10):772, 4, 6 passim.
  • 24. McLaren EA, Goldstein RE. The Photoshop Smile Design Technique. Compendium of continuing education in dentistry (Jamesburg, NJ : 1995). 2018;39(5):e17-e20.
  • 25. Stieber JC, Nelson T, Huebner CE. Considerations for use of dental photography and electronic media in dental education and clinical practice. Journal of dental education. 2015;79(4):432-8.
  • 26. Wander P. Dental photography in record keeping and litigation. British dental journal. 2014;216(4):207-8.
There are 26 citations in total.

Details

Primary Language English
Subjects Dentistry
Journal Section Research
Authors

Gediz Geduk 0000-0002-9650-2149

Murat İçen

Şükriye Ece Geduk This is me

Publication Date August 31, 2021
Submission Date November 20, 2019
Published in Issue Year 2021 Volume: 8 Issue: 2

Cite

Vancouver Geduk G, İçen M, Geduk ŞE. Using Photoshop Program in Reducing Motion and Noise Artifacts On Cone Beam Ct. Selcuk Dent J. 2021;8(2):359-66.