Abstract
The integration of AI technologies in medical image analysis has significantly transformed diagnostic capabilities, providing more accurate and reliable tools across various imaging modalities, including X-ray, CT, MRI, and ultrasound. Advancements in image classification, object detection, segmentation, and image registration have enabled improved detection, diagnosis, and monitoring of numerous medical conditions. Convolutional neural networks (CNNs) have been particularly instrumental in detecting diseases such as skin conditions, eye disorder s, and cancers, while object detection techniques have enhanced the localization and identification of abnormalities like lung nodules and tumors. Segmentation models have refined the delineation of anatomical structures, facilitating precise evaluations of organs and tumors. AI-driven image registration methods have also revolutionized the alignment of images from different modalities and times, improving treatment planning and disease monito