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License: GNU General Public License v3.0
Code for DARTS: DenseUnet-based Automatic Rapid Tool for brain Segmentation
License: GNU General Public License v3.0
Probably forgot to upload define_loss_score.py module:
hello,freesurfer
Previously, rh.white and rh.aparc.2009s.annot were used to generate vertex_id
and vertex_label,
'
surface = Surface.read_triangular('rh.white')
surface.load_annotation_file('rh.aparc.a2009s.annot')
with open("rhlabels.txt","w") as f:
for vertex_index, vertex in enumerate(surface.vertices):
vertex_label_index = surface.annotation.vertex_label_index[vertex_index]
vertex_label = surface.annotation.labels[vertex_label_index]
#print(vertex_index, vertex, vertex_label)
#f.write("vertex_index:{} vertexlabel:{} \n".format(vertex_index,
vertex_label))
f.write("vertex_index:{} vertex_label:{}\n".format(vertex_index,
vertex_label))
'
the output:vertex_index:0 vertexlabel:Label(name=S_precentral-sup-part, index=70, color=#1514c8)
after some algorthm: vertex_index:0 label_index=71
and the label_index obtained after a certain algorithm was updated to replace the vertex_labe_index in rh.aparc.2009s.annot, and then load the result with freeview. But I don't know how to replace the vertex_label_index value in .annot file?
Folks, you forgot to put the default --model_wts_path
in your Google Drive Link.
FileNotFoundError: [Errno 2] No such file or directory: './saved_model_wts/dense_unet_back2front_finetuned.pth'
Folks, pip install DARTSeg
should install all required modules by this software such as torch
, torchvision
etc. To make that happen, you should define a setup.py
file at the root directory which will be used by pip to install dependencies.
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