Algum is a web application developed at Carnegie Mellon University for generating Diamond filters using machine learning on marked up images.
The Algum website has moved again — from cumulonimbus.diamond.cs.cmu.edu to algum.cmusatyalab.org. An automatic redirection has been set up on the old site, but check if you have any bookmarks that link to the old name.
We will soon be migrating Algum to a virtual machine running on faster hardware. Now that Algum has its own hostname, we can do this at will, without having to ask you to update your bookmarks again.
Use tags to identify a subset of available images, after selecting an image a Deepzoom viewer is used to view the image. From this view it is also possible to navigate to any tasks that have labeled the image.
The Algum website has been moved from kohinoor.diamond.cs.cmu.edu to cumulonimbus.diamond.cs.cmu.edu. An automatic redirection has been set up on the old site, but check if you have any bookmarks that link to the old server.
Aside from the unpronounceable name, the new machine has considerably better specifications, 8 CPU cores, 8Gb of memory, and 1TB of available diskspace, plus several empty drivebays to add extra disks as needed.
It is now possible to upload a zip archive file containing slide data in any format that is supported by OpenSlide (Trestle, Hamamatsu, Mirax, Aperio and generic TIFF formats).
After upload you can double-click on the slide thumbnail to start an embedded OpenSeadragon viewer to pan and zoom over the full slide.
Tasks, Labels and Image data have been imported from the old site. However any existing users will need to reset their password before they can log in.
You can reset your password by following this link and entering your email address. You will then be sent an email containing your username and a temporary link through which a new password can be set.