Merge branch 'main' into testing/wrapper

Author: IvanARashid

.gitignore

@@ -1,8 +1,8 @@
 .idea*
 .github*
 __pycache__/
-
-
+*.nii.gz
+bvals.txt
 # Unit test / coverage reports
 .tox/
 .coverage

conftest.py

@@ -0,0 +1,145 @@
+import pytest
+import pathlib
+import json
+import csv
+# import datetime
+
+
+def pytest_addoption(parser):
+    parser.addoption(
+        "--SNR",
+        default=[100],
+        nargs="+",
+        type=int,
+        help="Evaluation test SNR",
+    )
+    parser.addoption(
+        "--ricianNoise",
+        default=False,
+        type=bool,
+        help="Use Rician noise, non-rician is gaussian",
+    )
+    parser.addoption(
+        "--algorithmFile",
+        default="tests/IVIMmodels/unit_tests/algorithms.json",
+        type=str,
+        help="Algorithm file name",
+    )
+    parser.addoption(
+        "--dataFile",
+        default="tests/IVIMmodels/unit_tests/generic.json",
+        type=str,
+        help="Default data file name",
+    )
+    parser.addoption(
+        "--saveFileName",
+        default="",
+        type=str,
+        help="Saved results file name",
+    )
+    parser.addoption(
+        "--rtol",
+        default=1,
+        type=float,
+        help="Relative tolerance",
+    )
+    parser.addoption(
+        "--atol",
+        default=1,
+        type=float,
+        help="Absolute tolerance",
+    )
+    parser.addoption(
+        "--fitCount",
+        default=10,
+        type=int,
+        help="Number of fits to perform on the same parameters",
+    )
+    parser.addoption(
+        "--saveDurationFileName",
+        default="",
+        type=str,
+        help="Saved duration results file name",
+    )
+
+
+@pytest.fixture(scope="session")
+def save_file(request):
+    filename = request.config.getoption("--saveFileName")
+    if filename:
+        current_folder = pathlib.Path.cwd()
+        filename = current_folder / filename
+        # print(filename)
+        # filename.unlink(missing_ok=True)
+        filename = filename.as_posix()
+        with open(filename, "w") as csv_file:
+            writer = csv.writer(csv_file, delimiter=',')
+            writer.writerow(("Algorithm", "Region", "SNR", "index", "f", "Dp", "D", "f_fitted", "Dp_fitted", "D_fitted"))
+            # writer.writerow(["", datetime.datetime.now()])
+    return filename
+
+@pytest.fixture(scope="session")
+def save_duration_file(request):
+    filename = request.config.getoption("--saveDurationFileName")
+    if filename:
+        current_folder = pathlib.Path.cwd()
+        filename = current_folder / filename
+        # print(filename)
+        # filename.unlink(missing_ok=True)
+        filename = filename.as_posix()
+        with open(filename, "w") as csv_file:
+            writer = csv.writer(csv_file, delimiter=',')
+            writer.writerow(("Algorithm", "Region", "SNR", "Duration [us]", "Count"))
+            # writer.writerow(["", datetime.datetime.now()])
+    return filename
+
+@pytest.fixture(scope="session")
+def rtol(request):
+    return request.config.getoption("--rtol")
+
+
+@pytest.fixture(scope="session")
+def atol(request):
+    return request.config.getoption("--atol")
+
+@pytest.fixture(scope="session")
+def fit_count(request):
+    return request.config.getoption("--fitCount")
+
+@pytest.fixture(scope="session")
+def rician_noise(request):
+    return request.config.getoption("--ricianNoise")
+
+
+def pytest_generate_tests(metafunc):
+    if "SNR" in metafunc.fixturenames:
+        metafunc.parametrize("SNR", metafunc.config.getoption("SNR"))
+    if "ivim_algorithm" in metafunc.fixturenames:
+        algorithms = algorithm_list(metafunc.config.getoption("algorithmFile"))
+        metafunc.parametrize("ivim_algorithm", algorithms)
+    if "algorithm_file" in metafunc.fixturenames:
+        metafunc.parametrize("algorithm_file", metafunc.config.getoption("algorithmFile"))
+    if "ivim_data" in metafunc.fixturenames:
+        data = data_list(metafunc.config.getoption("dataFile"))
+        metafunc.parametrize("ivim_data", data)
+    if "data_file" in metafunc.fixturenames:
+        metafunc.parametrize("data_file", metafunc.config.getoption("dataFile"))
+
+
+def algorithm_list(filename):
+    current_folder = pathlib.Path.cwd()
+    algorithm_path = current_folder / filename
+    with algorithm_path.open() as f:
+        algorithm_information = json.load(f)
+    return algorithm_information["algorithms"]
+
+def data_list(filename):
+    current_folder = pathlib.Path.cwd()
+    data_path = current_folder / filename
+    with data_path.open() as f:
+        all_data = json.load(f)
+
+    bvals = all_data.pop('config')
+    bvals = bvals['bvalues']
+    for name, data in all_data.items():
+        yield name, bvals, data

doc/code_contributions_record.csv

@@ -16,4 +16,5 @@ IVIM,Fitting,Linear fit,Linear fit for D with extrapolation for f. Supports unit
 IVIM,Fitting,sIVIM fit,NLLS of the simplified IVIM model (sIVIM). Supports units in mm2/s and µm2/ms,IAR_LundUniversity,TF2.4_IVIM-MRI_CodeCollection/src/original/IAR_LundUniversity/ivim_fit_method_modified_sivim.py,Modified by Ivan A. Rashid,Lund University,IvimModelsIVIM,tba,tbd,
 IVIM,Fitting,Segmented NLLS fitting,MATLAB code,OJ_GU,TF2.4_IVIM-MRI_CodeCollection/src/original/OJ_GU/,Oscar Jalnefjord,University of Gothenburg,IVIM_seg,https://doi.org/10.1007/s10334-018-0697-5,tbd,
 IVIM,Fitting,Bayesian,MATLAB code,OJ_GU,TF2.4_IVIM-MRI_CodeCollection/src/original/OJ_GU/,Oscar Jalnefjord,University of Gothenburg,IVIM_bayes,https://doi.org/10.1002/mrm.26783,tbd,
+IVIM,Fitting,Segmented NLLS fitting,Specifically tailored algorithm for NLLS segmented fitting,OJ_GU,TF2.4_IVIM-MRI_CodeCollection/src/original/OJ_GU/,Oscar Jalnefjord,University of Gothenburg,seg,https://doi.org/10.1007/s10334-018-0697-5,tbd,
 IVIM,Fitting,Linear fit,Linear fit for D and D* and f. Intended to be extremely fast but not always accurate,ETP_SRI,TF2.4_IVIM-MRI_CodeCollection/src/original/ETP_SRI/LinearFitting.py,Eric Peterson,SRI International,,,tbd,

phantoms/MR_XCAT_qMRI/sim_ivim_sig.py

@@ -8,7 +8,7 @@
 # code adapted from MAtlab code by Eric Schrauben: https://github.com/schrau24/XCAT-ERIC
 # This code generates a 4D IVIM phantom as nifti file
 
-def phantom(bvalue, noise, TR=3000, TE=40, motion=False, rician=False, interleaved=False):
+def phantom(bvalue, noise, TR=8000, TE=80, motion=False, rician=False, interleaved=False):
     np.random.seed(42)
     if motion:
         states = range(1,21)
@@ -367,7 +367,8 @@ def XCAT_to_MR_DCE(XCAT, TR, TE, bvalue, D, f, Ds, b0=3, ivim_cont = True):
     bvalue = np.array([0., 1, 2, 5, 10, 20, 30, 50, 75, 100, 150, 250, 350, 400, 550, 700, 850, 1000])
     noise = 0.0005
     motion = False
-    sig, XCAT, Dim, fim, Dpim, legend = phantom(bvalue, noise, motion=motion, interleaved=False)
+    interleaved = False
+    sig, XCAT, Dim, fim, Dpim, legend = phantom(bvalue, noise, motion=motion, interleaved=interleaved)
     # sig = np.flip(sig,axis=0)
     # sig = np.flip(sig,axis=1)
     res=np.eye(4)
@@ -402,12 +403,16 @@ def XCAT_to_MR_DCE(XCAT, TR, TE, bvalue, D, f, Ds, b0=3, ivim_cont = True):
     nifti_img = nib.Nifti1Image(sig, affine=res)  # Replace affine if necessary
     # Save the NIfTI image to a file
     nifti_img.header.set_data_dtype(np.float64)
-    if motion:
+    if not motion:
+        output_file = 'output.nii.gz'  # Replace with your desired output file name
+    elif interleaved:
         output_file = 'output_resp_int.nii.gz'  # Replace with your desired output file name
     else:
-        output_file = 'output.nii.gz'  # Replace with your desired output file name
+        output_file = 'output_resp.nii.gz'  # Replace with your desired output file name
+
     nib.save(nifti_img, output_file)
 
+
     nifti_img = nib.Nifti1Image(XCAT, affine=res)  # Replace affine if necessary
     # Save the NIfTI image to a file
     output_file = 'output_xcat.nii.gz'  # Replace with your desired output file name

phantoms/brain/README.md

@@ -0,0 +1,7 @@
+# Code for generating ivim phantoms of the brain
+
+Two sets of ground truth data are used for simulation:
+- Simulation in the diffusive regime (IVIM parameters D, f and D*): reference values from Ryghög et al. 2014 and b-values from Federau et al. 2012
+- Simulation in the ballistic regime (IVIM parameters D, f and vd): reference values and sequence parameters from Ahlgren et al. 2016
+
+The segmentation used by the simulations is the ICBM 2009a nonlinear symmetric 3T atlas (https://nist.mni.mcgill.ca/icbm-152-nonlinear-atlases-2009/), the same as in e.g. ASLDRO (https://asldro.readthedocs.io/en/stable/).

phantoms/brain/ground_truth/ballistic.bval

@@ -0,0 +1 @@
+0 10 20 30 40 50 60 70 80 90 100 120 140 160 180 200 10 20 30 40 50 60 70 80 90 100 120 140 160 180 200

phantoms/brain/ground_truth/ballistic.cval

@@ -0,0 +1 @@
+0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.471 0.666 0.816 0.942 1.054 1.154 1.247 1.333 1.414 1.490 1.632 1.763 1.885 1.999 2.107 

phantoms/brain/ground_truth/ballistic_calc_cval.py

@@ -0,0 +1,15 @@
+import os
+import numpy as np
+
+# Data from Ahlgren et al 2016 NMRinBiomed
+Delta = 7.5e-3 # 7.5 ms
+delta = 7.3e-3 # 7.3 ms
+
+# For DDE sequence we have
+# b = 2y^2G^2d^2(D-d/3), c = 2yGdD => c = sqrt(b 2D^2/(D-d/3))
+bval_file = os.path.join(os.path.dirname(__file__),'ballistic.bval')
+b = np.loadtxt(bval_file)
+c = np.sqrt(b*2*Delta**2/(Delta-delta/3))
+c[1:(c.size-1)//2+1] = 0 # flow compensated => c = 0
+cval_file = bval_file.replace('bval','cval')
+np.savetxt(cval_file,c,fmt='%.3f',newline=' ')

phantoms/brain/ground_truth/ballistic_groundtruth.json

@@ -0,0 +1,6 @@
+{
+    "D":[1.2e-3,0.98e-3,3e-3],
+    "f":[0.0243,0.0164,0],
+    "vd":[1.71,1.73,0],
+    "Db":1.75e-3
+}

phantoms/brain/ground_truth/diffusive.bval

@@ -0,0 +1 @@
+0 10 20 30 40 80 110 140 170 200 300 400 500 600 700 800 900