We developed Spotiflow with the mindset of making it useful and usable, and as such it comes in different flavors: one can use it as a Python API, as a CLI or with a GUI using our @napari.org plugin! Hopefully more integrations will come soon ;)
(7/N)

In a single molecule tracking experiment w/ Eftychia Kyriacou and Joachim Lingner from EPFL, Spotiflow allowed us to improve results by changing the input detections to Trackmate, showing that Spotiflow can be used as a drop-in replacement in existing workflows!
(5/N)

The context-awareness of Spotiflow allows for precise detection in challenging SNR conditions. This includes avoiding artifacts due to e.g. autofluorescence as we show with the beautiful P. dumerilii volumetric smFISH data from the Arendt and @ilastik-team.bsky.social teams @embl.org
(4/N)

Given an image or volume, Spotiflow uses a neural network to predict multiscale Gaussian heatmaps and the “stereographic flow” — a smooth embedding that maps the nD nearest-spot vector field to the (n+1)D sphere, avoiding issues at infinity and enabling precise localization
(2/N)