Flexible stage selection, tailored cnf to Jalapeno.

protocols/cnf_slice_to_volume.json

@@ -30,11 +30,11 @@
     },
     "general": {
         "verbosity": "debug",
-        "system": "macosx",
+        "system": "linux",
         "logfile": "/Users/inhuszar/bigmac/reg/tirl_slice_to_volume.log",
         "outdir": "/Users/inhuszar/bigmac/reg",
         "stages": [1, 2, 3, 4, 5, 2, 3, 4],
-	    "stage_index": 3,
+	    "stage_index": 0,
         "snapshot_ext": "png",
 	    "warnings": false
     },
@@ -52,13 +52,13 @@
                 "image": true,
                 "snapshot": true
             },
-            "visualise": true,
+            "visualise": false,
             "verbose": 4,
             "slab": {
                 "centre": [0, -4, 0],
                 "normal": [0, 1, 0],
                 "thickness": 3,
-                "inits": 7
+                "inits": 11
             },
             "iterations": 2,
             "scaling": [8, 4, 4, 2, 2, 1, 1],
@@ -138,8 +138,8 @@
                 "mask": true
             },
             "mask": {
-                "lthr": 0.1,
-                "uthr": 1
+                "lthr": 0.05,
+                "uthr": 0.95
             },
             "adaptive": {
                 "max_points": 32
@@ -161,8 +161,8 @@
                 "mask": true
             },
             "mask": {
-                "lthr": 0.1,
-                "uthr": 1
+                "lthr": 0.05,
+                "uthr": 0.95
             },
             "adaptive": {
                 "max_points": 32
@@ -186,8 +186,8 @@
             },
             "visualise": false,
             "mask": {
-                "lthr": 0.1,
-                "uthr": 1
+                "lthr": 0.05,
+                "uthr": 0.95
 	        }
         }
     }

protocols/tirl_slice_to_volume

@@ -4,7 +4,8 @@
 # This script is based on the Tensor Image Registration Library, which is part
 # of the FMRIB Software Library (FSL).
 # Author: Istvan N. Huszar, M.D. <istvan.huszar@dtc.ox.ac.uk>
-# Date: 1 Apr 2020
+# Date: 2 Apr 2020
+# Script version: 1.1
 
 
                                 # DEPENDENCIES
@@ -133,9 +134,23 @@ def run(cnf=None, **options):
     vol.centralise()
     logger.info(f"Loaded volume data: {vol.shape}")
 
+    # Is an alternative image available?
+    # If registration does not start form stage 1, load alternative input image.
+    # This should be a saved TImage file with an existing chain of
+    # transformations, ideally exported by this script at a later stage.
+    try:
+        img = tirl.load(p.slice.alternative)
+        assert isinstance(img, TImage)
+    except Exception:
+        alternative_image = False
+    else:
+        alternative_image = True
+        logger.info(f"Loaded slice data from alternative source: {img.shape}")
+
     # Load input images and perform pre-registration actions if the first
     # stage is stage 1.
-    if p.general.stages[0] == 1:
+    # if p.general.stages[0] == 1:
+    if not alternative_image:
 
         # Load slice (2D image)
         img = load_slice(p.slice.file, resolution=p.slice.resolution)
@@ -169,15 +184,6 @@ def run(cnf=None, **options):
         if p.slice.preview:
             img.preview()
 
-    # If registration does not start form stage 1, load alternative input image.
-    # This should be a saved TImage file with an existing chain of
-    # transformations, ideally exported by this script at a later stage.
-    else:
-        # Load alternative 2D image (slice)
-        img = tirl.load(p.slice.alternative)
-        assert isinstance(img, TImage)
-        logger.info(f"Loaded slice data from alternative source: {img.shape}")
-
     # Actions to perform on volume data
     # Actions are user-defined functions within the USER DEFINITIONS section of
     # this module. Actions can be chain-loaded to perform preparatory
@@ -233,7 +239,7 @@ def load_volume(volfile, resolution):
         raise FileNotFoundError(f"Volume data file does not exist: {volfile}")
 
     # Load volume
-    vol = TImage.fromfile(volfile, storage=p.volume.storage)
+    vol = TImage.fromfile(volfile, storage=p.volume.storage, dtype=np.float32)
 
     # Set mask
     if p.volume.mask.file is not None:
@@ -292,7 +298,7 @@ def load_slice(imfile, resolution):
         raise FileNotFoundError(f"Slice data file does not exist: {imfile}.")
 
     # Load slice
-    img = TImage.fromfile(imfile, storage=p.slice.storage)
+    img = TImage.fromfile(imfile, storage=p.slice.storage, dtype=np.float32)
 
     # Set mask
     if p.slice.mask.file is not None:
@@ -486,7 +492,7 @@ def update_registration_frame(img, cost, warpaxes, stparams):
         else:
             try:
                 # Convert points to y, x from x, y!
-                points = np.loadtxt(stparams.get("points", None))[:, ::-1]
+                points = np.loadtxt(stparams.get("points", ""))[:, ::-1]
             except Exception:
                 points = calculate_adaptive_control_points(img, cost, stparams)
             points = np.round(points).astype(np.int)
@@ -527,6 +533,7 @@ def calculate_adaptive_control_points(img, cost, stparams):
     t = AttrMap(stparams)
 
     # Create cost function map and a ROI mask for parcellation
+    print(img.data.dtype, np.min(img.data), np.max(img.data))
     mask = np.logical_and(img.data > t.mask.lthr, img.data <= t.mask.uthr)
     maskspec = t.export.mask
     if maskspec: