Recent advances in bioimaging have been transforming the way biological structures and events are visualized, quantified, and interpreted in preclinical research in bioengineering. Enabling analysis and visualization at structural, functional, and molecular scales, imaging technologies have been advancing with further integration with artificial intelligence, computational tools, and biological modeling. This chapter provides the author’s opinion on the current state of the art of bioimaging in preclinical research focusing on emerging scientific directions, indicating the expansion of established modalities such as magnetic resonance imaging, micro-computed tomography, ultrasound, and optical techniques with novel concepts and analytical/computational approaches. This editorial chapter summarizes the current key trends that include tailoring imaging approaches to specific experimental needs to address the need for quantification/visualization with the use of hybrid/multimodal imaging and contributions of artificial intelligence computer vision.

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Where Do We Stand in Preclinical Bioimaging: Synthesis and Perspectives

  • Ibrahim Fatih Cengiz,
  • Joaquim Miguel Oliveira,
  • Rui L. Reis

摘要

Recent advances in bioimaging have been transforming the way biological structures and events are visualized, quantified, and interpreted in preclinical research in bioengineering. Enabling analysis and visualization at structural, functional, and molecular scales, imaging technologies have been advancing with further integration with artificial intelligence, computational tools, and biological modeling. This chapter provides the author’s opinion on the current state of the art of bioimaging in preclinical research focusing on emerging scientific directions, indicating the expansion of established modalities such as magnetic resonance imaging, micro-computed tomography, ultrasound, and optical techniques with novel concepts and analytical/computational approaches. This editorial chapter summarizes the current key trends that include tailoring imaging approaches to specific experimental needs to address the need for quantification/visualization with the use of hybrid/multimodal imaging and contributions of artificial intelligence computer vision.