The Effect of Tube Current Variations on Cranium Radiograph Images Using the MATLAB Program
DOI:
10.29303/jppipa.v11i11.13042Published:
2025-12-03Downloads
Abstract
Matrix Laboratory (MATLAB) is a software based on matrices, which is easy to use for solving various mathematical and computing problems. This study aimed to determine how variations in tube current (mA) affect the radiographic image of the cranium using the MATLAB program and to assess the program's quantification of this effect. The sample in this study consisted of 3 volunteers who performed AP projection cranial radiography examinations with varying tube current at Pelamonia TK. II Hospital, Makassar. Each sample had the same treatment in patient preparation, examination position, examination projection, and the same exposure factor value, which differed only in the use of tube current values, where the volunteer 1 with 200 mA, the volunteer 2 with 250 mA and volunteer 3 with 320 mA. Measurement of the quality of the AP projection cranium image with tube current of 200 mA, the percentage was 96.11%. At 250 mA, the percentage was 95.00%; at 320 mA, it dropped to 92.78%. It was determined that the optimal tube current variation was 200 mA with the highest percentage in measuring the image quality (density, contrast, sharpness, and detail) of the AP projection Cranium against variations in tube current is almost perfect.
Keywords:
Cranium Radiography, Image, MATLAB Program, Tube currentReferences
Abdulrazzaq, A. Z., Mohammed, M. H., Ahmed, M. R. A., Ahmed, R. K. A., Majed, D. M., & Filipchuk, N. (2024). Advanced Data Processing in Computer Science: Leveraging MATLAB’s Computational Prowess and GUI Capabilities. 2024 36th Conference of Open Innovations Association (FRUCT), 56–65. https://doi.org/10.23919/FRUCT64283.2024.10749822
Archana, R., & Jeevaraj, P. E. (2024). Deep learning models for digital image processing: a review. Artificial Intelligence Review, 57(1). https://doi.org/10.1007/s10462-023-10631-z
Astolfo, A., Buchanan, I., Partridge, T., Kallon, G. K., Hagen, C. K., Munro, P. R. T., & Olivo, A. (2022). The effect of a variable focal spot size on the contrast channels retrieved in edge-illumination X-ray phase contrast imaging. Scientific Reports, 12(1). Retrieved from https://www.nature.com/articles/s41598-022-07376-0
Atina, A. (2019). Aplikasi Matlab pada Teknologi Pencitraan Medis. Jurnal Penelitian Fisika Dan Terapannya (JUPITER), 1(1), 28–34. https://doi.org/10.31851/jupiter.v1i1.3123
Bastos, A. D. L., & Nogueira, M. D. S. (2025). Image quality in diagnostic radiology: a guide to methodologies for radiologists. Radiologia Brasileira, 58. https://doi.org/10.1590/0100-3984.2024.0088-en
Biantari, I. D. A. S., Sutapa, G. N., Paramarta, I. B. A., Sandi, I. N., Suardana, P., Suandayani, N. K. T., & Setiawan, H. (2025). Pengaruh Variasi Arus Tabung (mA) Terhadap Kualitas Citra Pada Pesawat Computed Tomography (CT. Scan Di RSUD Bali Mandara. Kappa Journal, 9(1), 82–87. https://doi.org/10.29408/kpj.v9i1.29378
Bontrager, K. L., & Lampignano, J. (2013). Textbook of radiographic positioning and related Anatomy-E-Book. Elsevier Health Sciences.
Breitkreutz, D. Y., Weil, M. D., & Bazalova-Carter, M. (2020). External beam radiation therapy with kilovoltage x-rays. Physica Medica, 79, 103–112. https://doi.org/10.1016/j.ejmp.2020.11.001
Cappelli, P. H. (2015). Skill gaps, skill shortages, and skill mismatches: Evidence and arguments for the United States. ILR Review, 68(2), 251–290. https://doi.org/10.1177/0019793914564961
Fauber, T. L. (2020). Radiographic Imaging and Exposure-E-Book: Radiographic Imaging and Exposure-E-Book. In Elsevier Health Sciences. Elsevier Health Sciences.
Fauber, T. L. (2024). Fauber’s Radiographic Imaging and Exposure-E-Book. Elsevier Health Sciences.
Hasbi, N. A. (2024). Panduan Praktis Menulis Karya Tulis Kesehatan. PT. Bukuloka Literasi Bangsa.
Hassan, F. F. (2020). Assessment of X-Ray Tube Technical Factors: Tube Voltage and Exposure Time in Erbil Medical Imaging Centers. Disease and Diagnosis, 9(4), 144–147. https://doi.org/10.34172/ddj.2020.03
Huda, W., & Abrahams, R. B. (2015). Radiographic techniques, contrast, and noise in x-ray imaging. American Journal of Roentgenology, 204(2). https://doi.org/10.2214/AJR.14.13116
Idoko, P. I., Ezeamii, G. C., Idogho, C., Peter, E., Obot, U. S., & Iguoba, V. A. (2024). Mathematical modeling and simulations using software like MATLAB, COMSOL and Python. Magna Scientia Advanced Research and Reviews, 12(2), 062–095. https://doi.org/10.30574/msarr.2024.12.2.0181
Kjelle, E., & Chilanga, C. (2022). The assessment of image quality and diagnostic value in X-ray images: a survey on radiographers’ reasons for rejecting images. Insights into Imaging, 13(1). https://doi.org/10.1186/s13244-022-01169-9
Kleefeld, C., Castillo Lopez, J. P., Costa, P. R., Fitton, I., Mohamed, A., Pesznyak, C., & Tsapaki, V. (2024). Automated quality control solution for radiographic imaging of lung diseases. Journal of Clinical Medicine, 13(16). https://doi.org/10.3390/jcm13164967
Kurniasari, H. B., & Akhlis, I. (2012). Penerapan Pengolahan Citra Digital Dengan Matlab 7.1 Pada Citra Radiografi. Unnes Physics Journal, 1(1). Retrieved from https://shorturl.asia/PmIuB
Lee, J. Y., Lee, K. C., & Kweon, D. C. (2023). X-ray-acquired imaging and detection radiography system using digital radiography with a DSLR digital camera: preliminary results of a pilot study. Radiation Effects and Defects in Solids, 178(5–6), 654–667. https://doi.org/10.1080/10420150.2023.2166835
Malisngorar, M. S., Tunny, I. S., Niwele, A., Akhmadi, A., Rusli, R. H., Soumena, I., & Ariyanto, B. (2022). Pengaruh Variasi Nilai mA (Mili Ampere) dan s (Second) yang Berbeda Dengan Nilai mAs yang Sama Terhadap Paparan Medik yang Diterima Pasien. Jurnal Sains Dan Kesehatan, 6(1), 90–94. https://doi.org/10.57214/jusika.v6i1.522
Martinez, W. L., Martinez, A. R., & Solka, J. (2017). Exploratory data analysis with MATLAB. Chapman and Hall/CRC.
Mc Fadden, S., Roding, T., Vries, G., Benwell, M., Bijwaard, H., & Scheurleer, J. (2018). Digital imaging and radiographic practise in diagnostic radiography: An overview of current knowledge and practice in Europe. Radiography, 24(2), 137–141. https://doi.org/10.1016/j.radi.2017.11.004
Mustapha, M. T., Uzun, B., Ozsahin, D. U., & Ozsahin, I. (2021). A comparative study of X-ray based medical imaging devices. In Applications of Multi-Criteria Decision-Making Theories in Healthcare and Biomedical Engineering (pp. 163–180). Academic Press. https://doi.org/10.1016/B978-0-12-824086-1.00011-6
Nuraini, F. (2021). Perbandingan Informasi Anatomi Radiograf Cranium Proyeksi Ap Menggunakan Variasi Kv [Doctoral Dissertation: Universitas Awal Bros]. Retrieved from https://repository.univawalbros.ac.id/159/
Oborska-Kumaszyńska, D., & Wiśniewska-Kubka, S. (2010). Analog and digital systems of imaging in roentgenodiagnostics. Polish Journal of Radiology, 75(2). Retrieved from https://pmc.ncbi.nlm.nih.gov/articles/PMC3389874/
Oglat, A. A. (2022). Comparison of X-ray films in term of kVp, mA, exposure time and distance using Radiographic Chest Phantom as a radiation quality. Journal of Radiation Research and Applied Sciences, 15(4). https://doi.org/10.1016/j.jrras.2022.100479
Ou, X., Chen, X., Xu, X., Xie, L., Chen, X., Hong, Z., & Yang, H. (2021). Recent development in x-ray imaging technology: Future and challenges. Research. https://doi.org/10.34133/2021/9892152
Perez-Sanz, F., Navarro, P. J., & Egea-Cortines, M. (2017). Plant phenomics: An overview of image acquisition technologies and image data analysis algorithms. GigaScience, 6(11). https://doi.org/10.1093/gigascience/gix092
Prabhu, S., Naveen, D. K., Bangera, S., & Bhat, B. S. (2020). Production of x-rays using x-ray tube. Journal of Physics: Conference Series, 1712(1), 12036. https://doi.org/10.1088/1742-6596/1712/1/012036
Prakash, D., & Kotian, R. P. (2025). Standard X-Ray Tubes: Basic Principles, Types of X-Ray Tubes, and Routine Quality Control. In Fundamentals of X-ray Imaging: Basic Principles, Quality Control, Clinical Applications, and Safety (pp. 87–184). Springer Nature Singapore. https://doi.org/10.1007/978-981-96-7328-5_2
Purwanto, P., & Nastasia, W. (2022). Analysis of the effect of tube and mas voltage variations on contrast in digital radiographic systems. Jurnal Ilmiah Kesehatan Sandi Husada, 11(2), 308–320. https://doi.org/10.35816/jiskh.v11i1.750
Robertson, I. D., Thrall, D. E., & Nelson, N. C. (2024). Digital radiographic imaging. Textbook of Veterinary Diagnostic Radiology, 22–37. Retrieved from https://shorturl.asia/8J6N9
Routh, O. U. (2016). Matrix Algorithms in MATLAB. Academic Press.
Sari, A. W., & Fransiska, E. (2018). Pengaruh faktor eksposi dengan ketebalan objek pada pemeriksaan foto thorax terhadap gambaran radiografi. Journal of Health. Retrieved from https://shorturl.asia/K9i0u
Seeram, E. (2019). Computed radiography: physics and technology. In Digital Radiography: Physical Principles and Quality Control (pp. 41–63). Springer Singapore. https://doi.org/10.1007/978-981-13-3244-9_3
Sugiyono. (2019). Metode Penelitian Kuantitatif, Kualitatif dan R&D. Bandung: PT Alfabeta.
Susilo, W., B., S., & Kusminarto. (2013). Aplikasi Perangkat Lunak berbasis Matlab Untuk Pengukuran Radiograf Digital. Jurnal Pendidikan Fisika Indonesia, 9(1). https://doi.org/10.15294/jpfi.v9i1.2584
Thayalan, K. (2020). Medical X-ray Film Processing. Jaypee Brothers Medical Publishers.
Utami, A. P., & Istiqomah, A. N. (2023). The Influence of X-Ray Tube Current-Time Variations Toward Signal to Noise Ratio (SNR) in Digital Radiography: A Phantom Study. Applied Mechanics and Materials, 913, 121–129. https://doi.org/10.4028/p-ldt93t
Yamashita, K., Higashino, K., Hayashi, H., Takegami, K., Hayashi, F., Tsuruo, Y., & Sairyo, K. (2021). Direct measurement of radiation exposure dose to individual organs during diagnostic computed tomography examination. Scientific Reports, 11(1). Retrieved from https://www.nature.com/articles/s41598-021-85060-5
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