The article "Multimodal Bioimaging across Disciplines and Scales: Challenges, Opportunities, and Breaking Down Barriers" by Johanna Bischof et al. discusses the advancements and challenges in multimodal bioimaging, a technique that integrates multiple imaging modalities to provide a comprehensive view of biological structures and processes. The authors highlight the potential of multimodal bioimaging to revolutionize spatial biology by combining the strengths of different imaging approaches, such as microscopy, molecular imaging, structural imaging, and spectroscopy. They categorize multimodal bioimaging into direct correlative and indirect approaches, emphasizing the need for colocation or post-acquisition integration of data from different modalities. The article addresses several key challenges in multimodal bioimaging, including hardware and sample preparation, data analysis, and the integration with complementary spatial 'omics' approaches. It emphasizes the importance of developing multimodal contrast agents, improving data registration and fusion, and leveraging machine learning for advanced data analytics. The authors also stress the need for dedicated infrastructure, community support, and training to lower the barriers to broader adoption of multimodal bioimaging techniques. The article concludes with recommendations for advancing and adopting multimodal bioimaging, including improving seamless integration, leveraging machine learning, and fostering community-driven approaches to democratize access to advanced imaging technology. The authors highlight the importance of coordinated research infrastructures, such as Euro-BioImaging ERIC, in facilitating the development and application of multimodal bioimaging techniques.The article "Multimodal Bioimaging across Disciplines and Scales: Challenges, Opportunities, and Breaking Down Barriers" by Johanna Bischof et al. discusses the advancements and challenges in multimodal bioimaging, a technique that integrates multiple imaging modalities to provide a comprehensive view of biological structures and processes. The authors highlight the potential of multimodal bioimaging to revolutionize spatial biology by combining the strengths of different imaging approaches, such as microscopy, molecular imaging, structural imaging, and spectroscopy. They categorize multimodal bioimaging into direct correlative and indirect approaches, emphasizing the need for colocation or post-acquisition integration of data from different modalities. The article addresses several key challenges in multimodal bioimaging, including hardware and sample preparation, data analysis, and the integration with complementary spatial 'omics' approaches. It emphasizes the importance of developing multimodal contrast agents, improving data registration and fusion, and leveraging machine learning for advanced data analytics. The authors also stress the need for dedicated infrastructure, community support, and training to lower the barriers to broader adoption of multimodal bioimaging techniques. The article concludes with recommendations for advancing and adopting multimodal bioimaging, including improving seamless integration, leveraging machine learning, and fostering community-driven approaches to democratize access to advanced imaging technology. The authors highlight the importance of coordinated research infrastructures, such as Euro-BioImaging ERIC, in facilitating the development and application of multimodal bioimaging techniques.