Artificial Intelligence in X-Ray imaging: advances, challenges, and future directions

Corrigendum Notice: A corrigendum has been issued for this article and is included at the end of this document. Referred to by: “M. Kanli and A. Ece, “Artificial Intelligence in X-Ray imaging: advances, challenges, and future directions”, tbusphys, vol. 2, no. 3, p. 0018, Sept. 2024. doi: 10.54355/tbusphys/2.3.2024.0018”. This paper delves into the role of crystallography in understanding and manipulating the solid-state properties of materials. Crystallography, the study of atomic and molecular structures within crystals, is crucial for advancing materials science, particularly in fields like metallurgy, pharmaceuticals, and semiconductor technology. This paper highlights the techniques employed in crystallography, including X-ray diffraction (XRD), neutron diffraction, and electron microscopy, which allow for precise determination of crystal structures and properties. Furthermore, it discusses the applications of crystallography in designing and analyzing solid materials, such as developing new alloys, optimizing drug formulations, and enhancing the performance of electronic devices. Despite significant advancements, challenges persist, including the need for more sophisticated tools to study complex and disordered systems. This paper concludes by identifying future directions for research, emphasizing the integration of crystallography with computational methods to further understand and engineer solid materials.