Compute the watershed, initially for the extraction of sulcal pits as described in:
Auzias, G, Brun, L, Deruelle, C, Coulon, O, Deep sulcal landmarks: algorithmic and conceptual improvements in the definition and extraction of sulcal pits, NeuroImage, 2015.
During the flooding, the shallowest basin is merged with the deeper one if R inf thr and D inf ThD;
After the end of the flooding, if A inf ThA then merge the basin with its neighbor with which it shares the longest border.
input_mesh: Hemisphere White Mesh ( input )
DPF_texture: DPF texture ( input )
mask_texture: Cingular pole texture ( optional, input )
thresh_dist: Float ( input )
group_average_Fiedler_length: Float ( input )
thresh_area: Float ( input )
group_average_surface_area: Float ( input )
thresh_ridge: Float ( input )
pits_texture: pits texture ( output )
noisypits_texture: noisy pits texture ( output )
ridges_texture: ridges texture ( output )
basins_texture: basins texture ( output )
Toolbox : Cortical Surface
User level : 0
Identifier :
Mesh_watershed
File name :
brainvisa/toolboxes/cortical_surface/processes/anatomy/tools/Mesh_watershed.py
Supported file formats :
input_mesh :GIFTI file, GIFTI file, MESH mesh, MNI OBJ mesh, PLY mesh, TRI meshDPF_texture :GIFTI file, GIFTI file, Texturemask_texture :GIFTI file, GIFTI file, Texturepits_texture :GIFTI file, GIFTI file, Texturenoisypits_texture :GIFTI file, GIFTI file, Textureridges_texture :GIFTI file, GIFTI file, Texturebasins_texture :GIFTI file, GIFTI file, Texture