Merge pull request #27 from JaneliaSciComp/algorithm_dev

updated defaults for easifish_registration_pipeline

bigstream/align.py

@@ -6,7 +6,6 @@
 from bigstream.transform import apply_transform, compose_transform_list
 from bigstream.metrics import patch_mutual_information
 from bigstream import features
-from scipy.spatial import cKDTree
 import cv2
 
 
@@ -1210,14 +1209,13 @@ def alignment_pipeline(
              'deform':lambda **c: deformable_align(*a, **{**b, **c})[1],}
 
     # loop over steps
-    initial_transform_count = len(static_transform_list)
+    new_transforms = []
     for alignment, arguments in steps:
         arguments = {**kwargs, **arguments}
-        arguments['static_transform_list'] = static_transform_list
-        static_transform_list.append(align[alignment](**arguments))
+        arguments['static_transform_list'] = static_transform_list + new_transforms
+        new_transforms.append(align[alignment](**arguments))
 
     # return in the requested format
-    new_transforms = static_transform_list[initial_transform_count:]
     if return_format == 'independent':
         return new_transforms
     elif return_format == 'compressed':

bigstream/application_pipelines.py

@@ -84,14 +84,17 @@ def easifish_registration_pipeline(
         Any arguments you would like to pass to the global instance of
         bigstream.align.feature_point_ransac_affine_align. See the
         docstring for that function for valid parameters.
-        default : {'blob_sizes':[6, 20]}
+        default : {'alignment_spacing':np.min(fix_lowres_spacing)*4,
+                   'blob_sizes':[int(round(np.min(fix_lowres_spacing)*4)),
+                                 int(round(np.min(fix_lowres_spacing)*16))]}
 
     global_affine_kwargs : dict
         Any arguments you would like to pass to the global instance of
         bigstream.align.affine_align. See the docstring for that function
         for valid parameters.
-        default : {'shrink_factors':(2,),
-                   'smooth_sigmas':(2.5,),
+        default : {'alignment_spacing':np.min(fix_lowres_spacing)*4,
+                   'shrink_factors':(2,),
+                   'smooth_sigmas':(np.min(fix_lowres_spacing)*8,),
                    'optimizer_args':{
                        'learningRate':0.25,
                        'minStep':0.,
@@ -102,14 +105,15 @@ def easifish_registration_pipeline(
         Any arguments you would like to pass to the local instances of
         bigstream.align.feature_point_ransac_affine_align. See the
         docstring for that function for valid parameters.
-        default : {'blob_sizes':[6, 20]}
+        default : {'blob_sizes':same physical size as global_ransac values,
+                                but scaled to highres voxel grid}
 
     local_deform_kwargs : dict
         Any arguments you would like to pass to the local instances of
         bigstream.align.deformable_align. See the docstring for that function
         for valid parameters.
-        default : {'smooth_sigmas':(0.25,),
-                   'control_point_spacing':50.0,
+        default : {'smooth_sigmas':(np.min(fix_highres_spacing)*2,),
+                   'control_point_spacing':np.min(fix_highres_spacing)*128,
                    'control_point_levels':(1,),
                    'optimizer_args':{
                        'learningRate':0.25,
@@ -150,9 +154,14 @@ def easifish_registration_pipeline(
     mov_lowres = mov_lowres[...]
 
     # configure global affine alignment at lowres
-    a = {'blob_sizes':[6, 20]}
-    b = {'shrink_factors':(2,),
-         'smooth_sigmas':(2.5,),
+    alignment_spacing = np.min(fix_lowres_spacing)*4
+    blob_min = int(round(np.min(fix_lowres_spacing)*4))
+    blob_max = int(round(np.min(fix_lowres_spacing)*16))
+    a = {'alignment_spacing':alignment_spacing,
+         'blob_sizes':[blob_min, blob_max]}
+    b = {'alignment_spacing':alignment_spacing,
+         'shrink_factors':(2,),
+         'smooth_sigmas':(2*alignment_spacing,),
          'optimizer_args':{
              'learningRate':0.25,
              'minStep':0.,
@@ -181,9 +190,12 @@ def easifish_registration_pipeline(
     np.save(f'{write_directory}/affine.npy', aligned)
 
     # configure local deformable alignment at highres
-    a = {'blob_sizes':[6, 20]}
-    b = {'smooth_sigmas':(0.25,),
-         'control_point_spacing':50.0,
+    ratio = np.min(fix_spacing_lowres) / np.min(fix_spacing_highres)
+    blob_min = int(round(blob_min * ratio))
+    blob_max = int(round(blob_min * ratio))
+    a = {'blob_sizes':[blob_min, blob_max]}
+    b = {'smooth_sigmas':(2*np.min(fix_spacing_highres),),
+         'control_point_spacing':np.min(fix_spacing_highres)*128,
          'control_point_levels':(1,),
          'optimizer_args':{
              'learningRate':0.25,

bigstream/configure_irm.py

@@ -1,4 +1,4 @@
-import os, psutil
+import os
 import SimpleITK as sitk
 import bigstream.utility as ut
 

bigstream/level_set.py

@@ -119,6 +119,7 @@ def foreground_segmentation(
     smooth_sigmas=(8.,4.,2.),
     lambda2=20.,
     background=None,
+    return_largest_cc_only=True,
     mask=None,
     mask_smoothing=1,
 ):
@@ -151,6 +152,12 @@ def foreground_segmentation(
         An estimate of the average background intensity value. If None, it will
         automatically be estimated from the image using level_set.estimate_background
 
+    return_largest_cc_only : bool (default: True)
+        If true, final mask is eroded, then connected components are found,
+        only the largest cc is dilated and retained. If false, the entire
+        final level set is returned, even if the topology changed (e.g. multiple
+        discontinuous regions were found)
+
     mask : binary nd-array (default: None)
         Optional initialization for the level set. Must be the same shape as image.
 
@@ -183,9 +190,10 @@ def foreground_segmentation(
         )
 
     # basic topological correction
-    mask = binary_erosion(mask, iterations=2)
-    mask = largest_connected_component(mask)
-    mask = binary_dilation(mask, iterations=2)
+    if return_largest_cc_only:
+        mask = binary_erosion(mask, iterations=2)
+        mask = largest_connected_component(mask)
+        mask = binary_dilation(mask, iterations=2)
     mask = binary_fill_holes(mask).astype(np.uint8)
 
     # ensure output is on correct grid

bigstream/stitch.py

@@ -13,7 +13,6 @@
 from distributed import Event
 import time
 import os
-import psutil
 import aicspylibczi
 from ngff_zarr import to_ngff_image, to_multiscales, to_ngff_zarr
 

bigstream/transform.py

@@ -2,7 +2,7 @@
 import SimpleITK as sitk
 import bigstream.utility as ut
 from bigstream.configure_irm import interpolator_switch
-import os, psutil
+import os
 from scipy.ndimage import map_coordinates
 
 

bigstream/utility.py

@@ -9,6 +9,7 @@
 import h5py
 from ClusterWrap.decorator import cluster
 from zarr import blosc
+import psutil
 
 
 def skip_sample(image, spacing, ss_spacing):

setup.py

@@ -2,7 +2,7 @@
 
 setuptools.setup(
     name="bigstream",
-    version="1.2.1",
+    version="1.2.4",
     author="Greg M. Fleishman",
     author_email="[email protected]",
     description="Tools for distributed alignment of massive images",
@@ -25,6 +25,7 @@
         'numcodecs>=0.9.1',
         'fishspot>=0.2.3',
         'SimpleITK>=2.2.0',
-        'tifffile>=2022.10.10'
+        'tifffile>=2022.10.10',
+        'morphsnakes>=2.0.0'
     ]
 )