Ifmodels is currently a small Python package in its development stages. In the current development stage, ifmodels contains code that builds immunofluorescent neural models from stacks of immunofluorescent images obtained via confocal microscopy. These neural models are developed through four main steps: (1) performing edge detection of entire brain slices, (2) detecting registraion points based on external curvature, (3) registers slices to a provided universal atlas via an affine transformation, and (4) builiding a stack of images from the individual slices.
Ifmodels current state is the beginning of a much larger project with the goal of standardizing and quantifying immunofluorescent neural images for the preclinical space. The steps involved in the current package allow us better quantification of location information for our higher magnification images that will be registered to the whole brain slices in the future.
Currently doing development install only through TestPyPi.