Fusion of multi-modal medical images has transformed healthcare by overcoming the limitations of single-modality imaging, where modalities such as CT, MRI, PET, and SPECT provide complementary information. This review systematically traces the evolution of multi-modal medical image fusion from conventional mathematical models to state-of-the-art artificial intelligence (AI) techniques. We examine the transition from classical approaches---such as multiscale transformations, wavelet decompositions, and sparse representation---to modern deep learning methods, including convolutional neural networks, generative adversarial networks, and transformer architectures. Key limitations of existing met... More >

Biomedical Informatics and Smart Healthcare are helping to enhance and improve modern medicine and healthcare facilities by promoting technology-enhanced care and patient-centric approaches. This editorial primarily discusses the latest advancements in the fields of artificial intelligence, big data analytics, and IoT-enabled medical devices that are redefining medical workflows, diagnostics, and healthcare delivery. As the field evolves, biomedical informatics has enabled personalized patient treatment, real-time health tracking, and data-driven decision-making. The editorial also addresses ethical and regulatory concerns associated with this medical transformation, including issues related... More >

Medical imaging is an essential and valuable tool in modern medicine for providing essential details on the internal structures and functioning of the human body. Although very useful, the raw images obtained from medical imaging systems usually contain different types of artifacts and noise that might hide some essential diagnostic information. In this paper, the author details the conventional and non-conventional methods as well as sophisticated deep learning research methods used in improving the quality of healthcare images. The paper also delves into strategies designed to elevate the visual quality and interpretability in medical diagnostics. The paper includes some latest case studie... More >