Merge pull request #1225 from nipreps/enh/fa-masks-iqms

ENH: Add FA-based IQMs (nans percentage and degenerate percentage)

mriqc/interfaces/diffusion.py

@@ -128,6 +128,8 @@ class _DiffusionQCInputSpec(_BaseInterfaceInputSpec):
 class _DiffusionQCOutputSpec(TraitedSpec):
     cc_snr = traits.Dict
     efc = traits.Dict
+    fa_degenerate = traits.Float
+    fa_nans = traits.Float
     fber = traits.Dict
     fd = traits.Dict
     spikes_ppm = traits.Dict
@@ -205,7 +207,7 @@ def _run_interface(self, runtime):
         # Summary stats
         rois = {
             'fg': mskdata,
-            'bg': ~mskdata,
+            'bg': 1.0 - mskdata,
             'cc': ccdata,
             'wm': wmdata,
         }
@@ -220,7 +222,16 @@ def _run_interface(self, runtime):
             b_vectors=self.inputs.in_bvec,
         )
 
-        # Get cc mask data
+        fa_nans_mask = np.asanyarray(nb.load(self.inputs.in_fa_nans).dataobj) > 0.0
+        self._results['fa_nans'] = np.round(float(fa_nans_mask[mskdata > 0.5].mean()), 8) * 1e6
+
+        fa_degenerate_mask = np.asanyarray(nb.load(self.inputs.in_fa_degenerate).dataobj) > 0.0
+        self._results['fa_degenerate'] = np.round(
+            float(fa_degenerate_mask[mskdata > 0.5].mean()),
+            8,
+        ) * 1e6
+
+        # Get spikes-mask data
         spmask = np.asanyarray(nb.load(self.inputs.spikes_mask).dataobj) > 0.0
         self._results['spikes_ppm'] = dqc.spike_ppm(spmask)
 

mriqc/qc/diffusion.py

@@ -66,16 +66,27 @@
 SNR estimated in the Corpus Callosum (``cc_snr``)
     Worst-case and best-case signal-to-noise ratio (SNR) within the corpus callosum.
 
+.. _iqms_fa_nans:
+
+Number of not-a-number (NaN) values in the FA map (``fa_nan``)
+    Fraction of NaNs within the brain mask, in ppm.
+
+.. _iqms_fa_degenerate:
+
+Number of degenerate modeled voxels in the FA map (``fa_degenerate``)
+    Fraction of invalid FA values (i.e., outside the [0, 1] closed range) within
+    the brain mask, in ppm.
+
 IQMs relating artifacts and other
 ---------------------------------
 IQMs targeting artifacts that are specific of DWI images.
 
-.. _iqms_spike_percentage:
+.. _iqms_spike_ppm:
 
-Global and slice-wise spike percentages (``spike_perc``)
-    Voxels classified as spikes. The spikes mask is calculated by identifying
-    voxels with signal intensities exceeding a threshold based on standard
-    deviations above the mean.
+Global and slice-wise spike fractions (``spikes_ppm``)
+    Fractions of voxels classified as spikes (in parts-per-million, ppm).
+    The spikes mask is calculated by identifying voxels with signal intensities
+    exceeding a threshold based on standard deviations above the mean.
 
 """
 from __future__ import annotations