scholarly journals LAMA: automated image analysis for the developmental phenotyping of mouse embryos

Development ◽  
2021 ◽  
Vol 148 (18) ◽  
pp. dev192955
Author(s):  
Neil R. Horner ◽  
Shanmugasundaram Venkataraman ◽  
Chris Armit ◽  
Ramón Casero ◽  
James M. Brown ◽  
...  
Keyword(s):  
3D Imaging ◽  
Automated Image Analysis ◽  
Incomplete Penetrance ◽  
Imaging Data ◽  
Micro Computed Tomography ◽  
Sample Number ◽  
Automated Annotation ◽  
International Mouse Phenotyping Consortium ◽  
Automated Phenotyping ◽  
Wild Type Control

ABSTRACTAdvanced 3D imaging modalities, such as micro-computed tomography (micro-CT), have been incorporated into the high-throughput embryo pipeline of the International Mouse Phenotyping Consortium (IMPC). This project generates large volumes of raw data that cannot be immediately exploited without significant resources of personnel and expertise. Thus, rapid automated annotation is crucial to ensure that 3D imaging data can be integrated with other multi-dimensional phenotyping data. We present an automated computational mouse embryo phenotyping pipeline that harnesses the large amount of wild-type control data available in the IMPC embryo pipeline in order to address issues of low mutant sample number as well as incomplete penetrance and variable expressivity. We also investigate the effect of developmental substage on automated phenotyping results. Designed primarily for developmental biologists, our software performs image pre-processing, registration, statistical analysis and segmentation of embryo images. We also present a novel anatomical E14.5 embryo atlas average and, using it with LAMA, show that we can uncover known and novel dysmorphology from two IMPC knockout lines.

scholarly journals LAMA: Automated image analysis for developmental phenotyping of mouse embryos

2020 ◽  
Author(s):  
Neil R. Horner ◽  
Shanmugasundaram Venkataraman ◽  
Ramón Casero ◽  
James M. Brown ◽  
Sara Johnson ◽  
...  
Keyword(s):  
3D Imaging ◽  
Automated Analysis ◽  
Automated Image Analysis ◽  
Micro Ct ◽  
Imaging Data ◽  
Micro Computed Tomography ◽  
International Mouse Phenotyping Consortium ◽  
Population Average ◽  
Fast Solution ◽  
Ct Data

AbstractAdvanced 3D imaging modalities such as micro computed tomography (micro-CT), high resolution episcopic microscopy (HREM), and optical projection tomography (OPT) have been readily incorporated into high-throughput phenotyping pipelines, such as the International Mouse Phenotyping Consortium (IMPC). Such modalities generate large volumes of raw data that cannot be immediately harnessed without significant resources of manpower and expertise. Thus, rapid automated analysis and annotation is critical to ensure that 3D imaging data is able to be integrated with other multi-dimensional phenotyping data. To this end, we present an automated computational mouse phenotyping pipeline called LAMA, based on image registration, which requires minimal technical expertise and human input to use. Designed predominantly for developmental biologists, our software performs image pre-processing, registration, statistical and gene function annotation, and segmentation of 3D micro-CT data. We address several limitations of current methods and create an easy to use, fast solution application for mouse embryo phenotyping. We also present a highly granular, novel anatomical E14.5 (14.5 days post coitus) atlas of a population average that integrates with our pipeline to allow a range of dysmorphologies to be automatically annotated as well as results from the validation of the pipeline.

MicroCT protocols for scanning of embryos and juvenile Hexaplex trunculus v1

2021 ◽  
Author(s):  
Eva Chatzinikolaou ◽  
Kleoniki Keklikoglou
Keyword(s):  
Computed Tomography ◽  
High Resolution ◽  
3D Imaging ◽  
Imaging Technique ◽  
Ct Scanning ◽  
Micro Ct ◽  
Micro Computed Tomography ◽  
Gastropod Species ◽  
Biological Studies ◽  
Hexaplex Trunculus

Micro-computed tomography (micro-CT) is a high-resolution 3D-imaging technique which is now increasingly applied in biological studies focusing on taxonomy and functional morphology. The creation of virtual representations of specimens can increase availability of otherwise underexploited and inaccessible samples. This protocol aims to standardise micro-CT scanning procedures for embryos and juveniles of the marine gastropod species Hexaplex trunculus.

scholarly journals Assessing model mismatch and model selection in a Bayesian uncertainty quantification analysis of a fluid-dynamics model of pulmonary blood circulation

2020 ◽  
Vol 17 (173) ◽  
pp. 20200886
Author(s):  
L. Mihaela Paun ◽  
Mitchel J. Colebank ◽  
Mette S. Olufsen ◽  
Nicholas A. Hill ◽  
Dirk Husmeier
Keyword(s):  
Model Selection ◽  
Mean Squared Error ◽  
Formal Model ◽  
Circulation Model ◽  
Noise Model ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Imaging Data ◽  
Micro Computed Tomography ◽  
Model Mismatch

This study uses Bayesian inference to quantify the uncertainty of model parameters and haemodynamic predictions in a one-dimensional pulmonary circulation model based on an integration of mouse haemodynamic and micro-computed tomography imaging data. We emphasize an often neglected, though important source of uncertainty: in the mathematical model form due to the discrepancy between the model and the reality, and in the measurements due to the wrong noise model (jointly called ‘model mismatch’). We demonstrate that minimizing the mean squared error between the measured and the predicted data (the conventional method) in the presence of model mismatch leads to biased and overly confident parameter estimates and haemodynamic predictions. We show that our proposed method allowing for model mismatch, which we represent with Gaussian processes, corrects the bias. Additionally, we compare a linear and a nonlinear wall model, as well as models with different vessel stiffness relations. We use formal model selection analysis based on the Watanabe Akaike information criterion to select the model that best predicts the pulmonary haemodynamics. Results show that the nonlinear pressure–area relationship with stiffness dependent on the unstressed radius predicts best the data measured in a control mouse.

scholarly journals Development of a bent Laue beam-expanding double-crystal monochromator for biomedical X-ray imaging

2014 ◽  
Vol 21 (3) ◽  
pp. 479-483 ◽  
Author(s):  
Mercedes Martinson ◽  
Nazanin Samadi ◽  
George Belev ◽  
Bassey Bassey ◽  
Rob Lewis ◽  
...  
Keyword(s):  
Beam Quality ◽  
Dynamic Imaging ◽  
Micro Ct ◽  
Imaging Data ◽  
Micro Computed Tomography ◽  
Double Crystal ◽  
Double Crystal Monochromator ◽  
X Ray Imaging ◽  
Beam Expander ◽  
Vertical Beam

The Biomedical Imaging and Therapy (BMIT) beamline at the Canadian Light Source has produced some excellent biological imaging data. However, the disadvantage of a small vertical beam limits its usability in some applications. Micro-computed tomography (micro-CT) imaging requires multiple scans to produce a full projection, and certain dynamic imaging experiments are not possible. A larger vertical beam is desirable. It was cost-prohibitive to build a longer beamline that would have produced a large vertical beam. Instead, it was proposed to develop a beam expander that would create a beam appearing to originate at a source much farther away. This was accomplished using a bent Laue double-crystal monochromator in a non-dispersive divergent geometry. The design and implementation of this beam expander is presented along with results from the micro-CT and dynamic imaging tests conducted with this beam. Flux (photons per unit area per unit time) has been measured and found to be comparable with the existing flat Bragg double-crystal monochromator in use at BMIT. This increase in overall photon count is due to the enhanced bandwidth of the bent Laue configuration. Whilst the expanded beam quality is suitable for dynamic imaging and micro-CT, further work is required to improve its phase and coherence properties.

scholarly journals Constructing and optimizing 3D atlases from 2D data with application to the developing mouse brain

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
David M Young ◽  
Siavash Fazel Darbandi ◽  
Grace Schwartz ◽  
Zachary Bonzell ◽  
Deniz Yuruk ◽  
...  
Keyword(s):  
Mouse Brain ◽  
3D Imaging ◽  
Developmental Stages ◽  
Brain Atlas ◽  
Imaging Data ◽  
Qualitative And Quantitative ◽  
Atlas Construction ◽  
Manual Curation ◽  
Developing Mouse Brain ◽  
2D Data

3D imaging data necessitate 3D reference atlases for accurate quantitative interpretation. Existing computational methods to generate 3D atlases from 2D-derived atlases result in extensive artifacts, while manual curation approaches are labor-intensive. We present a computational approach for 3D atlas construction that substantially reduces artifacts by identifying anatomical boundaries in the underlying imaging data and using these to guide 3D transformation. Anatomical boundaries also allow extension of atlases to complete edge regions. Applying these methods to the eight developmental stages in the Allen Developing Mouse Brain Atlas (ADMBA) led to more comprehensive and accurate atlases. We generated imaging data from 15 whole mouse brains to validate atlas performance and observed qualitative and quantitative improvement (37% greater alignment between atlas and anatomical boundaries). We provide the pipeline as the MagellanMapper software and the eight 3D reconstructed ADMBA atlases. These resources facilitate whole-organ quantitative analysis between samples and across development.

scholarly journals Impact of drying methods on the changes of fruit microstructure unveiled by X-ray micro-computed tomography

RSC Advances ◽  
2019 ◽  
Vol 9 (19) ◽  
pp. 10606-10624
Author(s):  
Kevin Prawiranto ◽  
Thijs Defraeye ◽  
Dominique Derome ◽  
Andreas Bühlmann ◽  
Stefan Hartmann ◽  
...  
Keyword(s):  
Computed Tomography ◽  
3D Imaging ◽  
Drying Methods ◽  
Micro Computed Tomography ◽  
Lagrangian Analysis ◽  
X Ray ◽  
Drying Conditions

Distinct evolution of fruit microstructure under different drying conditions were identified using a 3D imaging and Eulerian–Lagrangian analysis.

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