This study investigates the application of Convolutional Neural Networks (CNNs) combined with cloud storage solutions for the detection of brain tumors in MRI scans using DICOM images. The increasing volume of medical imaging data necessitates efficient and secure storage solutions, and cloud storage offers a scalable and secure platform for handling these large datasets. By leveraging the powerful image recognition capabilities of CNNs, this approach aims to enhance the accuracy and efficiency of brain tumor detection. DICOM images, the standard format for medical imaging, are utilized to ensure compatibility and high-quality imaging data. The integration of cloud storage facilitates seamless access and processing of MRI scans, while robust security measures protect patient data. The results indicate that this method significantly improves the diagnostic process, providing reliable and timely detection of brain tumors, and underscores the potential of combining CNN and cloud technologies in medical imaging.