Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
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Artificial intelligence (AI) has recently become a very popular buzzword, as a consequence of disruptive technical advances and impressive experimental results, notably in the field of image analysis and processing. In medicine, specialties where images are central, like radiology, pathology or oncology, have seized the opportunity and considerable efforts in research and development have been deployed to transfer the potential of AI to clinical applications. ⋯ In addition, we discuss the new trends and future research directions. This will help the reader to understand how AI methods are now becoming an ubiquitous tool in any medical image analysis workflow and pave the way for the clinical implementation of AI-based solutions.
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Over the last decade there has been an extensive evolution in the Artificial Intelligence (AI) field. Modern radiation oncology is based on the exploitation of advanced computational methods aiming to personalization and high diagnostic and therapeutic precision. The quantity of the available imaging data and the increased developments of Machine Learning (ML), particularly Deep Learning (DL), triggered the research on uncovering "hidden" biomarkers and quantitative features from anatomical and functional medical images. ⋯ However, most of them are using limited datasets and lack generalized applicability. In this study we review the basics of radiomics feature extraction, DNNs in image analysis, and major interpretability methods that help enable explainable AI. Furthermore, we discuss the crucial requirement of multicenter recruitment of large datasets, increasing the biomarkers variability, so as to establish the potential clinical value of radiomics and the development of robust explainable AI models.
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To perform a systematic review on the research on the application of artificial intelligence (AI) to imaging published in Italy and identify its fields of application, methods and results. ⋯ We are witnessing an unprecedented interest in AI applied to imaging in Italy, in a diversity of fields and imaging techniques. Further initiatives are needed to build common frameworks and databases, collaborations among different types of institutions, and guidelines for research on AI.
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An increasing number of magnetic resonance whole-body units operating at field strengths of 3T and beyond are currently installed in research institutions as well as clinical facilities. This review wants to describe the changes in physical properties at higher field strength and the resulting implications for clinical and experimental examinations of the whole body. An overview is provided on the resulting advantages and disadvantages for anatomical, functional and biochemical MR examinations in different regions of the body (except the brain). ⋯ Nearly quadratic increase of RF energy deposition with increasing field strengths results in clear limitations for some common sequence types which work without any problems at 1.5 T. New strategies with multi-channel RF excitation have the potential to overcome limitations due to RF inhomogeneities, but a few years of further technological development seem necessary. Many problems have to be solved in the near future regarding the variety of MR techniques and applications in all parts of the human body.