Computer Vision Laboratory
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Seeing the Light 

 

In this project, we use a cutting-edge microscope, a light sheet fluoresence microscope (or LSFM) to image cellular anatomy as plants grow. A key challenge with LSFM time series data is the huge volume of data produced. This requires new analysis methods to permit us to gain biological insight. One such problem is identifying formative divisions that give rise to anatomical patterns in 3D datasets of roots resolved over time. This project seeks to automatically identify particular anatomical changes in big datasets. With LSFM it is possible to acquire gigabytes of data per minute. Time course experiments can easily generate tens of gigabytes of data. This turns visualisation and analysis into a bottleneck. We will use machine learning approaches to allow new software to identify regions of interest within these datasets. We will build visualisation tools which will use the results of these approaches to allow biologists to navigate the data in meaningful ways, rather than blindly moving through the whole dataset. We will use these tools to investigate how root anatomy is altered in plants grown in low nutrient environments.

Funding Information

Seeing the Light is funded by a grant from the Biotechnology and Biological Sciences Research Council

Project Team

Andrew French

Anthony Bishopp

CVL Contact

For further information please contact Andrew French

 
 

 

 

 

 

 

Computer Vision Laboratory

The University of Nottingham
Jubilee Campus
Wollaton Road
Nottingham, NG8 1BB


telephone: +44 (0) 115 8466543
email:tony.pridmore@nottingham.ac.uk