Abstract
ABSTRACT This review addresses the disease diagnosis from brain, eye, and lung scan images based on non-invasive imaging technologies using the Internet of Medical Things (IoMT) and Artificial Intelligence (AI) systems, a topic that has been neglected in the recent literature. Combining imaging modalities with IoMT and AI is expected to enhance both medical diagnoses and personalized treatment plans. We searched various scientific databases for details on IoMT and AI in medical imaging technologies from 2019 to 2023, focusing on different imaging modalities. We investigated the performance of AI-based algorithms in imaging modalities such as X-ray, Computed Tomography, Magnetic Resonance Imaging, Positron Emission Tomography, and Optical Coherence Tomography using the following metrics: accuracy, precision, recall, sensitivity, specificity, and F-1 score, and then analyzed their balanced performance in six issues: enhancement of medical image quality, improvement of clinical diagnoses, support for clinical decision-making, consideration of input data, time efficiency, and data management. Advanced understanding of the IoMT and AI applications in medical imaging technologies would help identify unexplored opportunities and provide directions for future research to enhance the clinical applicability.
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