RamApp

#RamApp is a modern #free and web-based tool for the analysis of hyperspectral #data. By @CNR_IFN @Fisipolimi and #Datrix in the context of @CrimsonEU

[RamApp @RamApp_tool]

#RamApp is out! 🚨
We are excited to release the first publicly available #beta version of #RamApp: a #free web-based tool for the analysis of (not-only) #Raman maps
➡️Try it here: https://t.co/nfIj4ffxf8😍

[RamApp @RamApp_tool]

After a while, some updates from @RamApp_tool before summer #vacations ⛱️🌞🍹

[RamApp @RamApp_tool]

🚀 Big news: #RamApp has now hit 150+ users!
Thank you to everyone who's made RamApp their tool of choice for hyperspectral data analysis.
We're just getting started on this amazing journey!
#Thanks 🙏
@CNR_IFN @fisipolimi #Datrix

[RamApp @RamApp_tool]

Did you try the #Spectral_fitting function in #RamApp ? Just upload your reference spectrum - even from other sources - select the appropriate fitting function and that's it.
Here below the #apatite reference spectrum is detected in #vertebral tissue using Pearson correlation

[RamApp @RamApp_tool]

@RamApp_tool was presented today at #ICAVS12 in Krakow!
@andre_masella delivered a presentation in a session focused on #chemometrics and #machinelearning topics.
Thank you to all the attendees who joined us!

➡️https://t.co/Kxr1YZLzcq

[RamApp @RamApp_tool]

Then you can obviously subtract the background from your map. Please note: the spurious regions cleaned out by the "morphological cleaning" function won't be included in the background to be subtracted 3/3

[RamApp @RamApp_tool]

Hey #RamAppers, did you try "Optical substrate removal" + "Morphological cleaning" ?
These can provide 1) automatic detection/subtraction of background around your sample;
2) remove  spurious cells/objects in the FOV thus selecting relevant targets
➡️More info in the thread 1/3

[RamApp @RamApp_tool]

To do that: 1) select "optical substrate removal" on the left menu 2) perform/optimize a first substrate identification 3) open "advanced options" 4) activate "morphological cleaning" 5) optimize parameters (size of spurious objects / erode edges). Done! 2/3

[RamApp @RamApp_tool]

Directly from @MIT a new image produced by @RamApp_tool by @bresci_arianna
These are aggregated #living mouse #embryonic #stem #cells exiting from pluripotency and showing differentiation features.
Steps: despike, automatic optical substrate removal, single bands integration

[RamApp @RamApp_tool]

@AppavooLab @PolliDario @CrimsonEu Hi Krishen, actually RamApp is in principle able to process "any" type of hyperspectral data. We have just optimized it for Raman data but nothing prevents using it for other type of data. Just try! And do not hesitate to contact us for further help

[RamApp @RamApp_tool]

A second image from @RamApp_tool!
@morteza_beh @HemenHosseini are investigating #rice structures, cultivar-specific features and pesticide contam., using a home-built Raman microscope @CNR_IFN @fisipolimi
➡️#RamAppers, share and tag your images!
(more details in the description)

[RamApp @RamApp_tool]

Let's start sharing beautiful images from @RamApp_tool users
This is from #BenedettoArdini @fisipolimi: a mixture of #microplastics (20-100 µm) studied by a home-built widefield FT-based #Raman Microscope
➡️we invite all #RamAppers to share their images
@CristianManzon6