Quantitative MR - QC

setup.py

@@ -45,12 +45,14 @@
             'visualqc_diffusion=visualqc.__diffusion__:main',
             'visualqc_freesurfer=visualqc.__freesurfer__:main',
             'visualqc_alignment=visualqc.__alignment__:main',
+            'visualqc_quantitative=visualqc.__quantitative__:main',
             # shortcuts
             'vqct1=visualqc.__t1_mri__:main',
             'vqcfunc=visualqc.__func_mri__:main',
             'vqcdwi=visualqc.__diffusion__:main',
             'vqcfs=visualqc.__freesurfer__:main',
-            'vqcalign=visualqc.__alignment__:main'
+            'vqcalign=visualqc.__alignment__:main',
+            'vqcqmr=visualqc.__quantitative__:main'
         ]
     },
     include_package_data=True,

visualqc/__quantitative__.py

@@ -0,0 +1,14 @@
+from sys import version_info
+
+if version_info.major > 2:
+    from visualqc import quantitative
+else:
+    raise NotImplementedError('visualqc_quantitative requires Python 3 or higher!')
+
+def main():
+    "Entry point."
+
+    quantitative.cli_run()
+
+if __name__ == '__main__':
+    main()

visualqc/config.py

@@ -349,6 +349,28 @@
 alpha_background_slice_alignment = 1.0
 alpha_edge_overlay_alignment = 1.0
 
+## ----------------------------------------------------------------------------
+#          Quantitative MR
+## ----------------------------------------------------------------------------
+
+qmr_alignment_rating = OrderedDict(a='Aligned', o='Not aligned')
+default_qmr_alignment_ratings = tuple(qmr_alignment_rating.values())
+
+qmr_contrast_rating = OrderedDict(g='Good contrast', b='Bad contrast')
+default_qmr_contrast_ratings = tuple(qmr_contrast_rating.values())
+
+position_alignment_radio_button = [0.895, 0.55, 0.1, 0.19]
+position_contrast_radio_button = [0.895, 0.32, 0.1, 0.25]
+
+position_contrast_button = [0.905, 0.80, 0.08, 0.04]
+
+color_contrast_button = 'xkcd:maroon'
+color_contrast_axis = 'xkcd:purple'
+color_alignment_axis = 'xkcd:orange'
+
+position_annotate_fg_quantMR = [0.45, 0.5]
+annotate_fg_quantMR_properties = dict(fontsize=30, color='xkcd:pale orange')
+
 ## ----------------------------------------------------------------------------
 #          Groupwise comparison of registration/alignment
 ## ----------------------------------------------------------------------------

visualqc/diffusion.py

@@ -377,7 +377,7 @@ def init_getters(self):
         self.feature_extractor = diffusion_mri_features
 
         if 'BIDS' in self.in_dir_type.upper():
-            from bids.grabbids import BIDSLayout
+            from bids import BIDSLayout
             self.bids_layout = BIDSLayout(self.in_dir)
             self.units = diffusion_traverse_bids(self.bids_layout)
             # file name of each scan is the unique identifier,