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Embryonic Development

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Acquisition and reconstruction of 4D surfaces of axolotl embryos with the flipping stage robotic microscope.

Bio Systems
We have designed and constructed a Flipping Stage for a light microscope that can view the whole exterior surface of a 2 mm diameter developing axolotl salamander embryo. It works by rapidly inverting the bottom-heavy embryo, imaging it as it rights ...

Artificial intelligence and machine learning for human reproduction and embryology presented at ASRM and ESHRE 2018.

Journal of assisted reproduction and genetics
Sixteen artificial intelligence (AI) and machine learning (ML) approaches were reported at the 2018 annual congresses of the American Society for Reproductive Biology (9) and European Society for Human Reproduction and Embryology (7). Nearly every as...

Deep learning image recognition enables efficient genome editing in zebrafish by automated injections.

PloS one
One of the most popular techniques in zebrafish research is microinjection. This is a rapid and efficient way to genetically manipulate early developing embryos, and to introduce microbes, chemical compounds, nanoparticles or tracers at larval stages...

Development and evaluation of inexpensive automated deep learning-based imaging systems for embryology.

Lab on a chip
Embryo assessment and selection is a critical step in an in vitro fertilization (IVF) procedure. Current embryo assessment approaches such as manual microscopy analysis done by embryologists or semi-automated time-lapse imaging systems are highly sub...

Towards the automation of early-stage human embryo development detection.

Biomedical engineering online
BACKGROUND: Infertility and subfertility affect a significant proportion of humanity. Assisted reproductive technology has been proven capable of alleviating infertility issues. In vitro fertilisation is one such option whose success is highly depend...

Investigating the gene expression profiles of cells in seven embryonic stages with machine learning algorithms.

Genomics
The development of embryonic cells involves several continuous stages, and some genes are related to embryogenesis. To date, few studies have systematically investigated changes in gene expression profiles during mammalian embryogenesis. In this stud...

3D convolutional neural networks-based segmentation to acquire quantitative criteria of the nucleus during mouse embryogenesis.

NPJ systems biology and applications
During embryogenesis, cells repeatedly divide and dynamically change their positions in three-dimensional (3D) space. A robust and accurate algorithm to acquire the 3D positions of the cells would help to reveal the mechanisms of embryogenesis. To ac...

Mining of variables from embryo morphokinetics, blastocyst's morphology and patient parameters: an approach to predict the live birth in the assisted reproduction service.

JBRA assisted reproduction
Based on growing demand for assisted reproduction technology, improved predictive models are required to optimize in vitro fertilization/intracytoplasmatic sperm injection strategies, prioritizing single embryo transfer. There are still several obsta...

FlyIT: Drosophila Embryogenesis Image Annotation based on Image Tiling and Convolutional Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics
With the rise of image-based transcriptomics, spatial gene expression data has become increasingly important for understanding gene regulations from the tissue level down to the cell level. Especially, the gene expression images of Drosophila embryos...