Digital image processing and deep learning are important applications of computer science in medical imaging. These technologies enable computers to analyze images obtained from X-rays, computed tomography, and magnetic resonance imaging. Image processing algorithms can improve image quality, reduce noise, and highlight suspicious regions. Deep learning models can also learn from large collections of medical images to identify patterns associated with particular diseases. These tools may assist radiologists in detecting abnormalities and evaluating medical conditions. However, their reliability must be assessed through appropriate clinical testing, and final diagnostic decisions should involve qualified healthcare professionals.