ANALISA PERBEDAAN VARIASI RECON TYPE TERHADAP INFORMASI CITRA PADA PEMERIKSAAN CT SCAN KEPALA KASUS STROKE ISKEMIK
DOI:
https://doi.org/10.31004/jkt.v5i1.25986Keywords:
Filter kernel, recon type, informasi citraAbstract
Stroke merupakan salah satu disfungsi otak yang muncul secara tiba-tiba, dengan tanda dan gejala yang berlangsung selama periode 24 jam. Stroke iskemik merupakan suatu kondisi medis yang timbul akibat penyumbatan aliran darah dalam otak. Salah satu pemeriksaan penunjang untuk menegakan diagnosa stroke iskemik yaitu pemeriksaan CT Scan Kepala. Pada CT Scan ada beberapa parameter salah satunya yakni rekontruksi algorithma yang berupa filter kernel tetapi pada alat GE disebut Recon type, Filter kernel merupakan salah satu parameter CT Scan, penelitian ini fokus pada pengaruh pada Informasi Citra dalam CT scan dengan peningkatan kontras resolusi, resolusi spasial, serta pengurangan noise. Pemilihan filter kernel yang tepat dapat sangat mempengaruhi kualitas gambar yang dihasilkan. Tujuan dilakukannya penelitian ini untuk membandingkan dan menegetahui informasi citra dihasilkan dengan recon type yang berbeda. Penelitian ini dilakukan secara kuantitatif melalui metode eksperimen. Sampel terdiri 10 pasien yang mengalami stroke iskemik, dan subjek penelitian gambar CT Scan kepala. Variasi dilakukan pada setiap pasien dengan 3 jenis filter kernel untuk melihat efeknya. Hasil uji statistik menyatakan bahwa p value <0.05 maka variasi recon type filter smooth 1, smooth 2 dan smooth 3 menunjukkan perbedaan informasi citra CT Scan kepala pada kasus stroke iskemik. Variasi recon type smooth 3 disarankan untuk pemeriksaan CT Scan kepala kasus stroke karena hasil uji statistik menunjukkan bahwa itu memberikan informasi citra yang paling optimal.References
Aliah, A., Kuswara, F. F., Limoa, A., Wuysang, G., & Aulia, S. (2014). Ahmad, S.(2008). Kendalikan Stres dan Hipertensi, Raih Produktivitas.
Almuslimiati, A., Milvita, D., & Prasetio, H. (2019). Analisis Nilai Noise dari Citra Pesawat CT-Scan pada Beberapa Rekonstruksi Kernel dengan Variasi Slice Thickness. Jurnal Fisika Unand, 8(1), 57-63.
Bruce W. Long. Merrill’s Atlas of Radiographic Positioning and Procedure. Volume 2. Edisi 13. Elsevier. USA. 2016
Buhk, J. H., Laqmani, A., Von Schultzendorff, H. C., Hammerle, D., Sehner, S., Adam, G., ... & Regier, M. (2013, August). Intraindividual evaluation of the influence of iterative reconstruction and filter kernel on subjective and objective image quality in computed tomography of the brain. In RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren (Vol. 185, No. 08, pp. 741-748). © Georg Thieme Verlag KG.
Cauley, K. A., Hu, Y., & Fielden, S. W. (2021). Head CT: toward making full use of the information the X-rays give. American Journal of Neuroradiology, 42(8), 1362-1369.
Damasio, H. (2005). Human brain anatomy in computerized images. Oxford university press.
Didik Dwi Darmawan, Rasyid, Emi Murniati, Perbedaan Informasi Anatomi Dengan Variasi Rekontruksi Increment Pada Pemeriksaan CT Scan Kepala Dengan Kasus Stroke, Poltekes Semarang, 2020.
Furie, K. L., Kasner, S. E., Adams, R. J., Albers, G. W., Bush, R. L., Fagan, S. C., ... & Wentworth, D. (2011). Guidelines for the prevention of stroke in patients with stroke or transient ischemic attack: a guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke, 42(1), 227-276.
Hutami, I. A. P. A., Sutapa, G. N., & Paramarta, I. B. A. Analisis Pengaruh Slice Thickness Terhadap Kualitas Citra Pesawat CT Scan Di RSUD Bali Mandara. Jurnal Bulettin Fisika, 22.
Johnsen, A. M. S., Fenn, J. M., Henning, M. K., & Hauge, I. H. (2023). Optimization of chest CT protocols based on pixel image matrix, kernels and iterative reconstruction levels–A phantom study. Radiography, 29(4), 752-759.
Kofler, J. M., Yu, L., Leng, S., Zhang, Y., Li, Z., Carter, R. E., & McCollough, C. H. (2015). Assessment of Low-Contrast Resolution for the ACR CT Accreditation Program: What is the Impact of Iterative Reconstruction Journal of computer assisted tomography, 39(4), 619.
Mackin, D., Ger, R., Gay, S., Dodge, C., Zhang, L., Yang, J., & Jones, A. K. (2019). Matching and homogenizing convolution kernels for quantitative studies in computed tomography. Investigative radiology, 54(5), 288-295.
Mair, G., Boyd, E. V., Chappell, F. M., von Kummer, R., Lindley, R. I., Sandercock, P., & Wardlaw, J. M. (2015). Sensitivity and specificity of the hyperdense artery sign for arterial obstruction in acute ischemic stroke. Stroke, 46(1), 102-107.
McHugh, M. L. (2012). Interrater reliability: the kappa statistic. Biochemia medica, 22(3), 276-282.
Mohammadinejad, P., Mileto, A., Yu, L., Leng, S., Guimaraes, L. S., Missert, A. D., ... & Fletcher, J. G. (2021). CT noise-reduction methods for lower-dose scanning: strengths and weaknesses of iterative reconstruction algorithms and new techniques. Radiographics, 41(5), 1493-1508.
Seeram, E. (2016) Computed Tomography: Physical Principles, Clinical Applications, and Quality Control. In Radiology (FOURTH EDI, Vol. 194, Issue 3). Elsevier.
Setiyono, P. A., Rochmayanti, D., Kurniawan, A. N., & Setiawan, A. N. (2020, February). The optimization of mastoid CT image using windows and kernel reconstructions. In Journal of Physics: Conference Series (Vol. 1471, No. 1, p. 012015). IOP Publishing.
Sutrisno, N., Kusumaputra, P. A., Winarno, G., & Gunawati, S. (2021). Analisis Perbandingan Variasi 3 Filter pada Rekonstruksi Citra Pemeriksaan CT Scan Mastoid. JRI (Jurnal Radiografer Indonesia), 4(1), 60-65.
Rahmadi, D., Anam, C., Hidayanyo, E., & Naufal, A. (2023). Implementation of Standard Deviation Map (SDM) for an Automation of Spatial Resolution Measurements on Computed Tomography Images of ACR CT Accreditation Phantom.
Romans, L. (2018). Computed Tomography for Technologists: A comprehensive text. Lippincott Williams & Wilkins.
Wahyuni, S. N., Diartama, A. A. A., & Mughnie, B. (2022). PENGARUH VARIASI REKONSTRUKSI SLICE THICKNESS DAN FILTER KERNEL TERHADAP KUALITAS CITRA CT-SCAN KEPALA PADA KASUS STROKE ISKEMIK. Humantech: Jurnal Ilmiah Multidisiplin Indonesia, 2(2), 218-22
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