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I am interested in segmenting white matter (WM) tissue from a T1 brain sequence image containing tumor. I am sharing a code snippet as follows:
`# 0) Load native-space T1
t1_native = ants.image_read(str(t1_pth))
tumor_mask_native = ants.image_read(str(tumor_pth))
out_dir = output_dir
# 1) Run Deep Atropos WITH built-in preprocessing (works in template/MNI space)
da = antspynet.deep_atropos(t1_native,
do_preprocessing = True,
verbose = True,
use_spatial_priors = 0)
seg_mni = da["segmentation_image"] # label image (template/MNI space)
seg_probs = da["probability_images"] # list of 6 tissue probability images (template/MNI space)
wm_prob = seg_probs[2] # white matter probability map`
My main concern is with presence of tumor itself. Is the current implementation robust enough to handle such cases?
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