ENH purged extra method purely based on nifty-seg and nifty-reg

Author: SebastianoF

README.md

@@ -51,15 +51,11 @@ nis_app.manipulate_labels.relabel('my_input_folder_path/my_segm.nii.gz', 'my_out
 
 ### How to install (in development mode) 
 
-+ Install [NiftySeg](https://github.com/KCL-BMEIS/NiftySeg)
-+ Install [NiftyReg](https://github.com/KCL-BMEIS/niftyreg)
-+ Install [ITK-snap](http://www.itksnap.org/pmwiki/pmwiki.php?n=Downloads.SNAP3)
-
-**Note:** NiftySeg, NiftyReg and ITK-Snap are required only for advanced functions.
 
 + Install python requirements in requirements.txt with
     `pip install -r requirements.txt`
 in a [virtualenv](http://docs.python-guide.org/en/latest/dev/virtualenvs/).
+
 + Install NiLabels: the current version is not (yet) pip installable. It can be installed in development mode.
 To proceede, initialise a virtual environment and execute the following instructions:
 ```
@@ -71,6 +67,12 @@ pip install -e .
 In development mode every change made to your local code will be directly affecting the libray installed in the python distribution
 without the need of reinstalling.
 
++ For advanced method `symmetrise_wit_registration`, extra examples and quick arrays visualisation with ITK-snap you must
+    + Install [NiftySeg](https://github.com/KCL-BMEIS/NiftySeg)
+    + Install [NiftyReg](https://github.com/KCL-BMEIS/niftyreg)
+    + Install [ITK-snap](http://www.itksnap.org/pmwiki/pmwiki.php?n=Downloads.SNAP3)
+
+
 
 ### Documentations
 

examples/prototype_clean_a_segmentation.py

@@ -43,6 +43,7 @@
 pfi_differece_cleaned_non_cleaned = jph(pfo_output_folder, 'difference_half_cleaned_uncleaned.nii.gz')
 
 # ---- PRE-PROCESS ---- Malice for real manual segmentation input. Keep commented for the provided phantom examples.
+# Based on NiftySeg.
 
 cmd_ero  = 'seg_maths {} -ero 1 {}'.format(pfi_input_segmentation_noisy, pfi_input_segmentation_noisy)
 cmd_dil  = 'seg_maths {} -dil 1 {}'.format(pfi_input_segmentation_noisy, pfi_input_segmentation_noisy)

examples/simple_label_fusion.py

@@ -65,12 +65,12 @@
         list_pfi_segmentations = [jph(pfo_results_propagation, 'seg_nrig_ellipsoid' + str(k) + '_on_target.nii.gz') for k in range(1, 11)]
         list_pfi_warped = [jph(pfo_results_propagation, 'seg_nrig_ellipsoid' + str(k) + '_on_target.nii.gz') for k in range(1, 11)]
 
-        lm.fuse.seg_LabFusion('target.nii.gz', jph('results_label_fusion', 'output' + options_seg + '.nii.gz'),
-                              list_pfi_segmentations, options=options_seg)
+        lm.fuse.create_stack_for_labels_fusion('target.nii.gz', jph('results_label_fusion', 'output' + options_seg + '.nii.gz'),
+                                               list_pfi_segmentations, options=options_seg)
 
         # If something more sophisticated needs to be done, it returns the paths to the stacks of images:
         options_seg = '_test2'
-        list_paths = lm.fuse.seg_LabFusion('target.nii.gz', jph('results_label_fusion', 'output' + options_seg + '.nii.gz'),
-                              list_pfi_segmentations, list_pfi_warped, options=options_seg, prepare_data_only=True)
+        list_paths = lm.fuse.create_stack_for_labels_fusion('target.nii.gz', jph('results_label_fusion', 'output' + options_seg + '.nii.gz'),
+                                                            list_pfi_segmentations, list_pfi_warped, options=options_seg, prepare_data_only=True)
 
         print(list_paths)

nilabels/agents/agents_controller.py

@@ -5,7 +5,6 @@
 from nilabels.agents.intensities_manipulator import IntensitiesManipulator
 from nilabels.agents.measurer import LabelsMeasure
 from nilabels.agents.fuser import LabelsFuser
-from nilabels.agents.propagator import LabelsPropagator
 from nilabels.agents.symmetrizer import SegmentationSymmetrizer
 from nilabels.agents.checker import LabelsChecker
 from nilabels.agents.header_controller import HeaderController
@@ -48,7 +47,6 @@ def _set_attribute_agents(self):
         self.manipulate_shape       = ShapeManipulator(self._pfo_in, self._pfo_out)
         self.measure                = LabelsMeasure(self._pfo_in, self._pfo_out)
         self.fuse                   = LabelsFuser(self._pfo_in, self._pfo_out)
-        self.propagate              = LabelsPropagator(self._pfo_in, self._pfo_out)
         self.symmetrize             = SegmentationSymmetrizer(self._pfo_in, self._pfo_out)
         self.check                  = LabelsChecker(self._pfo_in, self._pfo_out)
         self.header                 = HeaderController(self._pfo_in, self._pfo_out)

nilabels/agents/fuser.py

@@ -15,19 +15,14 @@ def __init__(self, input_data_folder=None, output_data_folder=None):
         self.pfo_in = input_data_folder
         self.pfo_out = output_data_folder
 
-    def seg_LabFusion(self, pfi_target, pfi_result, list_pfi_segmentations, list_pfi_warped=None, options='-MV',
-                      prepare_data_only=False, seg_output_name='res_4d_seg', warp_output_name='res_4d_warp',
-                      output_tag=''):
+    def create_stack_for_labels_fusion(self, pfi_target, pfi_result, list_pfi_segmentations, list_pfi_warped=None,
+                                       seg_output_name='res_4d_seg', warp_output_name='res_4d_warp', output_tag=''):
         """
         Stack and fuse anatomical images and segmentations in a single command.
-        Based on NiftySeg if prepare_data_only is False.
         :param pfi_target: path to file to the target of the segmentation
         :param pfi_result: path to file where to store the result.
         :param list_pfi_segmentations: list of the segmentations to fuse
         :param list_pfi_warped: list of the warped images to fuse
-        :param options: simple option of NiftySeg, can be -MV -SBA or -STAPLE
-        :param prepare_data_only: Return the paths to the stack images, and does not call seg_LabFusion.
-             This can be set as True when some more sophistication on the methods is required.
         :param seg_output_name:
         :param warp_output_name:
         :param output_tag: additional tag output.
@@ -61,9 +56,5 @@ def seg_LabFusion(self, pfi_target, pfi_result, list_pfi_segmentations, list_pfi
             pfi_4d_warp = connect_path_tail_head(self.pfo_out, '{0}_{1}.nii.gz'.format(warp_output_name, output_tag))
             nib.save(im_4d_warp, pfi_4d_warp)
 
-        if not prepare_data_only:
-            cmd = 'seg_LabFusion -in {0} -out {1} {2}'.format(pfi_4d_seg, pfi_result, options)
-            os.system(cmd)
 
-        else:
-            return pfi_target, pfi_result, pfi_4d_seg, pfi_4d_warp
+        return pfi_target, pfi_result, pfi_4d_seg, pfi_4d_warp

nilabels/agents/propagator.py

@@ -63,6 +63,8 @@ def symmetrise_with_registration(self,
         labels value, it will spare you some time when set to True.
         :param coord: coordinate of the registration: in RAS, 'z' will symmetrise Left on Right.
         :return: symmetrised segmentation.
+        ---
+        NOTE: requires niftyreg.
         """
 
         pfi_in_anatomy = connect_path_tail_head(self.pfo_in, filename_anatomy)