A python interface to the rat brain atlas Purpose ------- Using the rat brain atlas... 1) construct 3d point clouds of various brain regions 2) lookup the area for a given location (ML, DV, AP coordinate) 3) grab the containing section image for a given location 4) plot a location on a flattened cortical surface Installation details -------------------- Due to copyright reasons, this module does not contain the eps files from the cd that comes with the rat brain atlas. These files are however required for the module to function. You can either pass in the path of the eps files to the necessary functions (such as Section.__init__) or copy the eps files (of at least the coronal sections) to ~/.atlas/eps. How to ------ get the section index for the containing section >>> atlas.py section 6.5 3.5 -7 plot a location on a section (show and save the plot) >>> atlas.py section 6.5 3.5 -7 -ps get the area for a location >>> atlas.py area 6.5 3.5 -7 get a point cloud of an area (saved to meshes/<area>.asc) [takes a while] >>> atlas.py points V2L -m plot a location on a flattened cortex >>> atlas.py cortex 6.5 3.5 -7 -ps Several calls to plot on a flattened cortical surface will go much faster if the area points are recomputed like so >>> atlas.py area -p area.p >>> atlas.py cortex <ML> <DV> <AP> -A area.p Notes ----- this is buggy and hacky as all heck what I wanted was to generate a 3d mesh of a selected brain area from a stack of labeled brain atlas images Steps: 1) take eps files of a brain atlas 2) find location of a selected area label within each eps file 3) render eps file to bitmap format 4) find pixels that correspond to the border of the selected area 5) map image to brain coordinates 6) output 3d brain coordinates for border of selected area at each slice 7) use meshlab to generate mesh from points this is terribly hacky and relied on: 3) manually generating the mesh using ball-pivoting in meshlab what I would really like is to 2) make a more flexible mapping for all atlas slices 3) automatically generate mesh Meshlab ------- 1) load in a points file for an area (ex: V1.asc) 2) simplify the points: Filter -> Cleaning -> Merge: ~.05 world units 3) save as mesh (ex: .ply) 4) reload 3) mesh the points: Filter -> Remeshing -> Surface Reconstruction (ball pivoting): ~.5 world units (or .7 for V2L) 5) close holes 5) smooth: Filter -> Smoothing -> Laplace Smooth: 2 iterations 6) save as mesh (ex: .ply)