ANALISIS PERBANDINGAN SNR DAN CNR PADA CITRA DIGITAL RADIOGRAPHY KEPALA NON KONTRASMENGUNAKAN METODE PENGOLAHAN CITRA PHYTON - Kalpin, Kalpin; Anshor Nugroho; Muhammad Fakhrurreza (Bajang Institute, 2025)
Background: This study compares SNR and CNR in non-contrast head X-rays using Python. Head image quality is crucial due to its complex anatomical structure and the importance of small details in determining a diagnosis. Python is used to objectively analyze image clarity, read medical data, calculate SNR and CNR values, and display the results visually. This research is expected to help physicians obtain clearer images, accelerate diagnoses, and improve the quality of radiology services. Methods: This research was conducted at the Radiology Laboratory of Aisyiyah University Yogyakarta from March to May 2025. The subjects used were not live patients, but rather cranium phantoms, which are artificial models of human heads typically used for training or research to ensure safety. In this study, three different X- ray settings were used: 70 kV 10 mAs, 75 kV 12 mAs, and 80 kV 15 mAs. Each setting produced head X-rays with varying levels of brightness and sharpness. The images were saved in a medical-specific format called DICOM. Next, the images were analyzed using the Python programming language through the Google Colab platform. This analysis was carried out to calculate two important things: SNR (Signal-to-Noise Ratio), which describes how clear the image signal is compared to interference or