Skip to content

Filter f extremes and deduplicate generic signals #139

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
oliverchampion wants to merge 1 commit into
base: main
Choose a base branch
from
Open

Filter f extremes and deduplicate generic signals #139

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
16 changes: 15 additions & 1 deletion phantoms/MR_XCAT_qMRI/sim_ivim_sig.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -451,15 +451,29 @@ def parse_bvalues_file(file_path):

voxel_selector_fraction = 0.5
D, f, Ds = contrast_curve_calc()
ignore = np.isnan(D)
ignore = np.logical_or(np.logical_or(np.isnan(D),f<0.03),f>0.97)
generic_data = {}
seen_combinations = set()

for level, name in legend.items():
if len(ignore) > level and ignore[level]:
continue
selector = XCAT == level
voxels = sig[selector]
if len(voxels) < 1:
continue
D_val = np.median(Dim[selector], axis=0)
f_val = np.median(fim[selector], axis=0)
Dp_val = np.median(Dpim[selector], axis=0)

combo = (tuple(np.atleast_1d(D_val)),
tuple(np.atleast_1d(f_val)),
tuple(np.atleast_1d(Dp_val)))

if combo in seen_combinations:
continue

seen_combinations.add(combo)
signals = np.squeeze(voxels[int(voxels.shape[0] * voxel_selector_fraction)]).tolist()
generic_data[name] = {
'noise': noise,
Expand Down
Loading