Deep learning, especially Convolutional Neural Networks (CNNs), is shaping the future of data-driven problem solving. From text-related problems like speech generation, content writing, etc to vision tasks like image classification, object detection, CNNs are widely used. In the past few years, numerous advanced CNN architectures have been proposed like Graph CNNs, Attention-based CNNs, Complex-valued CNNs etc. In this article I will be summarizing my research paper published here, wherein a novel complex-valued CNN-based deep learning model is proposed for medical image denoising. Medical imaging has revolutionized the health sector by assisting medical professionals in several ways, including disease diagnosis, treatment, and risk prediction.