Nuclei detection should be more stable across regions

This does a better job of detecting the average color of the area being
analyzed to reduce individual tile effects.  It also fixes a potential
infinite loop in a degenerate case.

histomicstk/cli/NucleiDetection/NucleiDetection.py

@@ -187,7 +187,7 @@ def detect_nuclei_with_dask(ts, tile_fgnd_frac_list, it_kwargs, args,
  return nuclei_list
 
 
-def main(args):
+def main(args): # noqa
 
  # Flags
  invert_image = False
@@ -220,7 +220,7 @@ def main(args):
  'tile_size': {'width': args.analysis_tile_size},
  'scale': {'magnification': args.analysis_mag},
  'tile_overlap': {'x': tile_overlap, 'y': tile_overlap},
- 'style': {args.style},
+ 'style': args.style,
  }
 
  # retrieve frame
@@ -230,7 +230,7 @@ def main(args):
  msg = 'The given frame value is not an integer'
  raise Exception(msg)
  else:
- it_kwargs['frame'] = args.frame
+ it_kwargs['frame'] = int(args.frame)
 
  #
  # Initiate Dask client
@@ -305,6 +305,28 @@ def main(args):
  src_mu_lab, src_sigma_lab = compute_reinhard_norm(
  args, invert_image=invert_image, default_img_inversion=default_img_inversion)
 
+ if src_mu_lab is None:
+ smallImage, _ = ts.getRegion(
+ output=dict(maxWidth=4096, maxHeight=4096), resample=False,
+ region=it_kwargs.get('region', {}),
+ format=large_image.tilesource.TILE_FORMAT_NUMPY,
+ frame=args.frame)
+ if len(smallImage.shape) == 2:
+ smallImage = np.resize(smallImage, (smallImage.shape[0], smallImage.shape[1], 1))
+ if smallImage.shape[2] < 3:
+ if default_img_inversion or invert_image:
+ smallImage = (np.iinfo(smallImage.dtype).max
+ if smallImage.dtype.kind == 'u'
+ else np.max(smallImage)) - smallImage
+ smallImage = np.repeat(smallImage[:, :, :1], 3, 2)
+ elif not default_img_inversion and invert_image:
+ smallImage = (np.iinfo(smallImage.dtype).max
+ if smallImage.dtype.kind == 'u'
+ else np.max(smallImage)) - smallImage
+ smallImage = smallImage[:, :, :3]
+ src_mu_lab, src_sigma_lab = htk_cnorm.reinhard_stats_rgb(smallImage)
+ print(src_mu_lab, src_sigma_lab)
+
  #
  # Detect nuclei in parallel using Dask
  #

histomicstk/preprocessing/color_normalization/__init__.py

@@ -6,7 +6,7 @@
 from .deconvolution_based_normalization import \
  deconvolution_based_normalization
 from .reinhard import reinhard
-from .reinhard_stats import reinhard_stats
+from .reinhard_stats import reinhard_stats, reinhard_stats_rgb
 
 # list out things that are available for public use
 __all__ = (
@@ -15,5 +15,6 @@
  'background_intensity',
  'reinhard',
  'reinhard_stats',
+ 'reinhard_stats_rgb',
  'deconvolution_based_normalization',
 )

histomicstk/preprocessing/color_normalization/reinhard_stats.py

@@ -82,3 +82,12 @@ def reinhard_stats(
  stats = ReinhardStats(Mu, Sigma)
 
  return stats
+
+
+def reinhard_stats_rgb(rgb_image):
+ rgb_pixels = np.reshape(rgb_image, (1, rgb_image.shape[0] * rgb_image.shape[1], 3))
+
+ Mu, Sigma = color_conversion.lab_mean_std(rgb_pixels)
+
+ # build named tuple for output
+ return collections.namedtuple('ReinhardStats', ['Mu', 'Sigma'])(Mu, Sigma)