Artificial Intelligence Techniques in Medical Imaging: A Systematic Review

This scientific review presents a comprehensive overview of medical imaging modalities and their diverse applications in artificial intelligence (AI)-based disease classification and segmentation. The paper begins by explaining the fundamental concepts of AI, machine learning (ML), and deep learning (DL). It provides a summary of their different types to establish a solid foundation for the subsequent analysis. The prmary focus of this study is to conduct a systematic review of research articles that examine disease classification and segmentation in different anatomical regions using AI methodologies. The analysis includes a thorough examination of the results reported in each article, extracting important insights and identifying emerging trends. Moreover, the paper critically discusses the challenges encountered during these studies, including issues related to data availability and quality, model generalization, and interpretability. The aim is to provide guidance for optimizing technique selection. The analysis highlights the prominence of hybrid approaches, which seamlessly integrate ML and DL techniques, in achieving effective and relevant results across various disease types. The promising potential of these hybrid models opens up new opportunities for future research in the field of medical diagnosis. Additionally, addressing the challenges posed by the limited availability of annotated medical images through the incorporation of medical image synthesis and transfer learning techniques is identified as a crucial focus for future research efforts

Contribution to a geodynamic reconstruction of the Anti-Atlas (Morocco) during Pan-African times with the emphasis on inversion tectonics and metallogenic activity at the Precambrian-Cambrian transition

International audienceNew geochronological analyses (U–Pb SIMS zircon ages) have yielded ages of 552 ± 5 Ma for the Bou Madine rhyolitic dome (Ougnat, eastern Anti-Atlas), 543 ± 9 Ma for the Tachkakacht rhyolitic dyke (Saghro–Imiter, eastern Anti-Atlas), and 531 ± 5 Ma for the Aghbar trachytic sill (Bou Azzer, central Anti-Atlas). Inherited zircon cores from the Aghbar trachytic sill and from the Bou Madine rhyolitic dome have been shown to be of Statherian age (ca. 1600–1800 Ma) and Palæoproterozoic (>2100 Ma) age, respectively, suggesting that a significantly older protolith underlies the Pan-African rocks in the Central and Eastern Anti-Atlas. Granodiorites and rhyolites from the Saghro–Imiter area have similar low 87Sr/86Sr (0.702–0.706) and 143Nd/144Nd (0.5116–0.5119) initial ratios, suggesting a mixture of mantle and lower crust sources. This can also be inferred from the low 187Os/188Os ratios obtained on pyrite crystals from the rhyolites. A recently published lithostratigraphic framework has been combined with these new geochemical and geochronological data, and those from the literature to produce a new reconstruction of the complex orogenic front that developed at the northern edge of the Eburnian West African craton during Pan-African times. Three Neoproterozoic magmatic series can be distinguished in the Anti-Atlas belt, i.e., high-K calc-alkaline granites, high-K calc-alkaline to shoshonitic rhyolites and andesites, and alkaline-shoshonitic trachytes and syenites, which have been dated at 595–570, 570–545 and 530 Ma, respectively. The accretion of the Pan-African Anti-Atlas belt to the West African super continent (WAC) was a four-stage event, involving extension, subduction, moderate collision and extension. The calc-alkaline magmatism of the subduction stage was associated with large-scale base metal and gold mineralisation. Metallogenic activity was greatest during the final extensional stage, at the Precambrian–Cambrian boundary. It is characterised by world-class precious metal deposits, base–metal porphyry and SEDEX-type occurrences