Applications of Nuclear Medicine in the Field of Molecular Imaging

Abstract

Author(s): Ji Jie, Liew Kai Bin, Wan Rosalina Wan Rosli

Nuclear medicine is a field of medical imaging that uses low dosages of radioactive material substances to detect certain developed conditions, including cancer, heart disease, and abnormalities. Nuclear medicine in depressed regions likewise faces challenges due to a lack of essential tools, like phantoms and essential radiation sources for quality equipment testing, radiation shielding and medical physics laboratories. Due to their complexity, Convolutional Neural Networks (CNN) can be used to diagnose bone metastasis in a binary and multiclass rating problem, though their accuracy strongly depends on the quality of medical developing images. Molecular Imaging (MI) is a rapidly growing area of biomedical research that allows for the imaging, analysis, and measurement of biological processes happening at the cellular and subcellular levels in entire living creatures, including patients. Hence, CNN-MI is a diagnostic method used in nuclear medicine that frequently detects anomalies early in developing a disease, decades preceding conventional tests. Diagnosing diseases in their earliest periods gives patients a higher chance of fully recovering. The energy source is provided physically in nuclear medicine and molecular imaging strategies, that radiation is absorbed into a target tissue, organ, and process and immediately detected using a transcending measure for providing data regarding the organ's and process's function and cellular activity. As a result, nuclear medicine finally provides a safe, painless, and costeffective way of gathering previously unavailable information that needed a more expensive and stressful diagnostic strategy.

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