About this Research Topic
Microphysiological systems (MPS), also known as organ-on-a-chip or tissue chip platforms, represent an innovative bioengineering approach aiming to replicate the intricate microenvironment of human organs in vitro. These miniature systems provide researchers with enhanced physiological relevance compared to traditional models, enabling high fidelity study of drug responses and disease mechanisms. A key element in the success of MPS is the ability to capture and analyze high-resolution images of cellular and tissue structures. Overall, the implementation of advanced image processing and analysis techniques in this field holds significant promise for advancing our understanding of human biology, disease pathology, and drug efficacy, ultimately paving the way for personalized medicine and therapeutic development.
This topic plans to explore recent advancements in image processing and analysis techniques tailored specifically for MPS, investigating novel methodologies for acquiring, processing, and interpreting multi-dimensional imaging data produced by these platforms. Contributions in this area may involve the development of automated image processing algorithms and pipelines to efficiently segment and quantify cellular features, including morphology, proliferation, and migration within tissue constructs. Manuscripts can address advanced image analysis tools designed to extract dynamic information such as cell-cell interactions, tissue biomechanics, and physiological responses from time-lapse imaging datasets.
Submissions to this topic can also tackle challenges related to image acquisition, such as optical aberrations, phototoxicity, and image artifacts, discussing strategies to mitigate these issues. Moreover, manuscripts may highlight the integration of machine learning and artificial intelligence approaches to improve the accuracy and speed of image analysis, facilitating rapid data interpretation and hypothesis generation.
This topic delves into Microphysiological Systems (MPS), also known as organ-on-a-chip or tissue chip platforms, which aim to mimic human organ microenvironments in vitro for studying drug responses and disease mechanisms. Central to the success of MPS is the ability to capture and analyze high-resolution images of cellular and tissue structures.
This Research Topic aims to provide a comprehensive, contemporary collection of research focusing on advancement in microphysiological systems. We welcome Original Research Articles, Reviews, Mini-Reviews, Systematic Reviews, Perspectives, Commentaries, Data notes, and technical notes, but are not limited to the following:
• In this topic, we seek to explore recent advancements in image processing and analysis techniques tailored for MPS, focusing on acquiring, processing, and interpreting multi-dimensional imaging data.
• Contributions may include automated methods to segment and quantify cellular features, advanced tools to extract dynamic information, and addressing challenges in image acquisition.
• Additionally, integration of machine learning and artificial intelligence algorithms to enhance image analysis speed and accuracy can be highlighted, with the overarching goal of advancing understanding in human biology, disease pathology, and drug efficacy, toward personalized medicine and therapeutic development.
This topic plans to explore recent advancements in image processing and analysis techniques tailored specifically for MPS, investigating novel methodologies for acquiring, processing, and interpreting multi-dimensional imaging data produced by these platforms. Contributions in this area may involve the development of automated image processing algorithms and pipelines to efficiently segment and quantify cellular features, including morphology, proliferation, and migration within tissue constructs. Manuscripts can address advanced image analysis tools designed to extract dynamic information such as cell-cell interactions, tissue biomechanics, and physiological responses from time-lapse imaging datasets.
Submissions to this topic can also tackle challenges related to image acquisition, such as optical aberrations, phototoxicity, and image artifacts, discussing strategies to mitigate these issues. Moreover, manuscripts may highlight the integration of machine learning and artificial intelligence approaches to improve the accuracy and speed of image analysis, facilitating rapid data interpretation and hypothesis generation.
This topic delves into Microphysiological Systems (MPS), also known as organ-on-a-chip or tissue chip platforms, which aim to mimic human organ microenvironments in vitro for studying drug responses and disease mechanisms. Central to the success of MPS is the ability to capture and analyze high-resolution images of cellular and tissue structures.
This Research Topic aims to provide a comprehensive, contemporary collection of research focusing on advancement in microphysiological systems. We welcome Original Research Articles, Reviews, Mini-Reviews, Systematic Reviews, Perspectives, Commentaries, Data notes, and technical notes, but are not limited to the following:
• In this topic, we seek to explore recent advancements in image processing and analysis techniques tailored for MPS, focusing on acquiring, processing, and interpreting multi-dimensional imaging data.
• Contributions may include automated methods to segment and quantify cellular features, advanced tools to extract dynamic information, and addressing challenges in image acquisition.
• Additionally, integration of machine learning and artificial intelligence algorithms to enhance image analysis speed and accuracy can be highlighted, with the overarching goal of advancing understanding in human biology, disease pathology, and drug efficacy, toward personalized medicine and therapeutic development.
Keywords: organ on a chip, Microphysiological systems, Machine learninig, Multi-Dimensional Imaging Data
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
