Imagining the future of bioimage analysis

Meijering, Erik; Carpenter, Anne E.; Peng, Hanchuan; Hamprecht, Fred A.; Olivo‐Marin, Jean‐Christophe

doi:10.1038/nbt.3722

Cited by 165 publications

(144 citation statements)

References 47 publications

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“…The pairwise similarity measures w i,j are computed using Euclidean norm between pairs of data points (x (1) …”

Section: Illustrative Examplementioning

confidence: 99%

“…In the absence of noise, this mapping from t to the 2D plane can be inverted as t ¼ (1) , x (2) ) by composition. In this example, y corresponds to the target modality that we would like to estimate.…”

Section: Illustrative Examplementioning

confidence: 99%

“…where a, b, c, d, e are constants, (1) and (2) are Gaussian noise sources and t is a real-valued parameter. The set of points (…”

Section: Illustrative Examplementioning

confidence: 99%

“…The need to synthesize data from different observations into coherent multivariable trajectories is discussed in multiple contexts, from physics to social sciences, but systematic approaches for accomplishing this task have yet to be established [1][2][3][4][5]. Here we address this task for imaging studies of developing tissues, where patterns of cell fates are established by complex regulatory networks [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

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Synthesizing developmental trajectories

Villoutreix

Andén

Lim

et al. 2017

Preprint

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Dynamical processes in biology are studied using an ever-increasing number of techniques, each of which brings out unique features of the system. One of the current challenges is to develop systematic approaches for fusing heterogeneous datasets into an integrated view of multivariable dynamics. We demonstrate that heterogeneous data fusion can be successfully implemented within a semi-supervised learning framework that exploits the intrinsic geometry of high-dimensional datasets. We illustrate our approach using a dataset from studies of pattern formation in Drosophila. The result is a continuous trajectory that reveals the joint dynamics of gene expression, subcellular protein localization, protein phosphorylation, and tissue morphogenesis. Our approach can be readily adapted to other imaging modalities and forms a starting point for further steps of data analytics and modeling of biological dynamics. Author summaryA wide range of problems in biology require analysis of multivariable dynamics in space and time. As a rule, the multiscale nature and complexity of real systems precludes simultaneous monitoring of all the relevant variables, and multivariable dynamics must be synthesized from partial views provided by different experimental techniques. We present a formal framework for accomplishing this task in the context of imaging studies of pattern formation in developing tissues.

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“…The pairwise similarity measures w i,j are computed using Euclidean norm between pairs of data points (x (1) …”

Section: Illustrative Examplementioning

confidence: 99%

Section: Illustrative Examplementioning

confidence: 99%

“…where a, b, c, d, e are constants, (1) and (2) are Gaussian noise sources and t is a real-valued parameter. The set of points (…”

Section: Illustrative Examplementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Synthesizing developmental trajectories

Villoutreix

Andén

Lim

et al. 2017

Preprint

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show abstract

“…Since high-quality images as well as hardware with high-throughput capabilities are available for imaging solutions, the bioimage informatics community is also strongly developing more sophisticated software solutions capable of obtaining information-rich measurements from acquired image data in an accurate and reproducible manner [12,13]. Besides a range of commercial software solutions [14], open-source software packages-such as Fiji/ImageJ [15], Tango [16], Icy [17], and CellProfiler [18]-have been reported over the last years.…”

Section: Introductionmentioning

confidence: 99%

Image-Based Histological Evaluation of Scaffold-Free 3D Osteoblast Cultures

Eggert

Tuebel

Foehr

et al. 2017

JFMK

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Abstract:The analysis of tissue network characteristics and cell distribution using histological methods is widely used. However, image analysis still relies on manual evaluation methods, known as semi-quantitative analysis, which are time-consuming and to a certain degree user-specific. For this reason, automated imaging processing methods have an enormous potential to increase sample processing and reduce the variation that is caused by a user-specific evaluation. This work demonstrates the feasibility of using a semi-automated image analysis process based on the open source software framework ImageJ and the plug-in Angiogenesis Analyzer to evaluate the quantitative degree of tissue damage within 3D cell constructs after mechanical loading. Within a proof-of-concept study, the semi-automated approach was applied to calculate the Node-to-Free Ratio (N/F-Ratio) and perform a strut analysis for histological evaluation of mechanically compressed samples of human osteoblast-derived 3D constructs. The N/F-Ratio revealed a median value of 1.29 for the control, whereas the values for the mechanically compressed samples decreased to 0.97 for 20% compression, 0.85 for 40%, and 0.86 for 60%. The strut analysis indicated a decrease of the connected branches with increasing compression rate. The newly developed and time-saving processing workflow was successfully established and can be carried out using available, open source software solutions.

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Curable Layered Double Hydroxide Nanoparticles‐Based Perfusion Contrast Agents for X‐Ray Computed Tomography Imaging of Vascular Structures

Tokudome

Poologasundarampillai

Tachibana

et al. 2021

Advanced NanoBiomed Research

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Imaging complex vascular structures by X‐ray microcomputed tomography (μ‐CT) is becoming vital for research purposes in pathology of vascular diseases. Acrylic‐based polymerizable resins are widely adopted for the contrast agent to prepare pathological specimens for imaging of vascular structures. For imaging of vascular structures at higher resolution, it is promising to develop inorganic‐type contrast agents with higher X‐ray attenuation coefficient as well as low viscosity, homogeneity, minimum shrinkage, curable (gellable) for replication, and low cost. Herein, a novel inorganic sol–gel system based on concentrated colloidal dispersion of NiAl layered double hydroxide (LDH) nanoparticles is described, allowing imaging of vascular structures at high resolution. NiAl LDH acts as nanofiller and alkaline catalyst to form a silica/LDH monolithic material with homogeneity from the nanoscale. Moreover, NiAl LDH nanoparticles contribute to the strong enhancement of the X‐ray attenuation. As a proof‐of‐concept, X‐ray μ‐CT imaging of the developed contrast agent in glass capillaries and of blood vessels of a human placenta and murine liver is demonstrated.

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Imagining the future of bioimage analysis

Cited by 165 publications

References 47 publications

Synthesizing developmental trajectories

Synthesizing developmental trajectories

Image-Based Histological Evaluation of Scaffold-Free 3D Osteoblast Cultures

Curable Layered Double Hydroxide Nanoparticles‐Based Perfusion Contrast Agents for X‐Ray Computed Tomography Imaging of Vascular Structures

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