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New Machine Learning Tools for 3D volume analysis

A new software tool has been developed by Computer Vision Lab PhD student Imanol Luengo as part of his studentship with the Diamond Light Source. The SuRVoS (Super-Region Volume Segmentation) Workbench is designed to facilitate the segmentation of complex biological datasets captured at the Diamond Light Source. With SuRVoS, a volume is first partitioned into super-regions and then interactively segmented by the user inputting training annotations. SuRVoS can then learn from and extend the annotations to the whole volume, a process that is currently five times faster than purely manual segmentation. The tool was recently published in the Journal of Structural Biology, and the tool appeared on the front cover.

Overview of SuRVoS: http://www.diamond.ac.uk/Science/Research/Highlights/2017/survos.html

Paper: http://www.sciencedirect.com/science/article/pii/S1047847717300308

Contact: imanol.luengo@nottingham.ac.uk; andrew.p.french@nottingham.ac.uk ; tony.pridmore@nottingham.ac.uk

structural biology

Posted on Wednesday 10th May 2017

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