Improvements to KymoButler
Hello everyone,
It has been less than a month since we released KymoButler and we already received great feedback that is helping us shape the future of our software.
It is with great pleasure that today we announce some big improvements to KymoButler:
The Deeper Neural Network is available now!
We optimised the Deep Neural Network from our paper to compute much faster, so we are now able to provide the full network for free on our cloud app. The new version is especially good at tracing very dense lines and the example below highlights the performance on a kymograph from actin speckle microscopy:
We believe this is going to improve analysis for many of you – please try it out now at our KymoButler page!
Support for kymographs with dark and light background is available now!
We announced this a few days ago on Twitter, but we think it’s worth repeating: KymoButler now works on kymographs with dark and light backgrounds.
If you tried to analyse white background images before, please try KymoButler again now.
Bidirectional KymoButler available soon!
We are making steady progress with our bidirectional KymoButler, which will enable you to follow molecules that move both forwards and backwards in kymographs (see an example on our Software page). Please stay tuned to our blog and follow us on Twitter to receive the latest news from us!
Working together
At deepMirror.ai, we aim to bring state-of-the-art AI-based technology to quantitative data analysis that for too long has relied on manual analysis. By training Deep Neural Networks, we can teach an AI to perform as well as an expert.
If your work would benefit from this kind of approach, get in touch with us and we will find the best solution for your specific problem.