Merge pull request #388 from GSTT-CSC/94-BC-kernel

Add command line option to change kernel size used in SNR task based on head or body coil.
GSTT-CSC · Nov 28, 2023 · c0ced4a · c0ced4a · github-actions · Nov 28, 2023
2 parents 2ac4bd0 + 2f4293f
commit c0ced4a
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Showing 2 changed files with 16 additions and 5 deletions.
diff --git a/hazenlib/__init__.py b/hazenlib/__init__.py
@@ -85,7 +85,7 @@
 
 Usage:
     hazen <task> <folder> [options]
-    hazen snr <folder> [--measured_slice_width=<mm>] [options]
+    hazen snr <folder> [--measured_slice_width=<mm>] [--coil=<head or body>] [options]
     hazen acr_snr <folder> [--measured_slice_width=<mm>] [--subtract=<folder2>] [options]
     hazen relaxometry <folder> --calc=<T1> --plate_number=<4> [options]
 
@@ -107,7 +107,6 @@
     --plate_number=<n>           Which plate to use for measurement: 4 or 5 (required)
 """
 
-
 import importlib
 import inspect
 import logging
@@ -196,7 +195,8 @@ def main():
     if arguments['snr'] or arguments['<task>'] == 'snr':
         selected_task = 'snr'
         task = init_task(selected_task, files, report, report_dir,
-                         measured_slice_width=arguments['--measured_slice_width'])
+                         measured_slice_width=arguments['--measured_slice_width'],
+                         coil=arguments['--coil'])
         result = task.run()
     elif arguments['acr_snr'] or arguments['<task>'] == 'acr_snr':
         selected_task = 'acr_snr'

diff --git a/hazenlib/tasks/snr.py b/hazenlib/tasks/snr.py
@@ -28,12 +28,23 @@ class SNR(HazenTask):
 
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
+
         # measured slice width is expected to be a floating point number
         try:
             self.measured_slice_width = float(kwargs["measured_slice_width"])
         except:
             self.measured_slice_width = None
 
+        # Determining kernel size based on coil choice. Values of 9 and 25 come from McCann 2013 paper.            
+        try:
+            coil = kwargs["coil"]
+            if coil is None or coil.lower() in ["hc", "head"]:
+                self.kernel_size = 9
+            elif coil.lower() in ["bc", "body"]:
+                self.kernel_size = 25
+        except: 
+            self.kernel_size=9
+
     def run(self) -> dict:
 
         results = self.init_result_dict()
@@ -134,10 +145,10 @@ def filtered_image(self, dcm: pydicom.Dataset) -> np.array:
         a = dcm.pixel_array.astype('int')
 
         # filter size = 9, following MATLAB code and McCann 2013 paper for head coil, although note McCann 2013 recommends 25x25 for body coil.
-        filter_size = 9
+
         # 9 for head coil, 25 for body coil
         # TODO make kernel size optional
-        filtered_array = ndimage.uniform_filter(a, filter_size, mode='constant')
+        filtered_array = ndimage.uniform_filter(a, self.kernel_size, mode='constant')
         return filtered_array
 
     def get_noise_image(self, dcm: pydicom.Dataset) -> np.array:
File	Stmts	Miss	Cover	Missing
hazenlib
ACRObject.py	107	11	90%	74, 77–79, 84–87, 125, 168–169
HazenTask.py	29	3	90%	41–43
__init__.py	57	15	74%	165, 196–200, 202–206, 208–210, 225–230, 234
exceptions.py	21	5	76%	17–21, 38
utils.py	189	43	77%	61, 65, 75, 80, 117, 124–129, 140, 143–150, 170–172, 190–192, 211–213, 222, 227, 233, 284, 287, 295–300, 303, 346, 355, 371
hazenlib/tasks
acr_geometric_accuracy.py	119	62	48%	42–86, 96–121, 134–168
acr_ghosting.py	107	42	61%	35–51, 77–79, 109–111, 145–187
acr_slice_position.py	136	48	65%	47–68, 194–241
acr_slice_thickness.py	136	60	56%	34–53, 162–224
acr_snr.py	136	58	57%	46, 51–92, 102, 172–182, 216–231, 264–281
acr_spatial_resolution.py	206	68	67%	59–86, 131, 174, 187–196, 278–330
acr_uniformity.py	81	32	60%	38–56, 112–138
ghosting.py	151	51	66%	19–36, 51, 113–114, 118, 128–129, 155–157, 174–176, 222–259
relaxometry.py	291	89	69%	207–208, 210, 221–224, 230–236, 268–312, 353, 387–405, 580, 626–628, 695, 769–791, 809–824
slice_position.py	124	40	68%	26, 31–62, 114–115, 141, 221, 229–247
slice_width.py	352	52	85%	36–38, 42, 107, 166–187, 441, 446–447, 453, 458, 516–517, 767–809
snr.py	175	71	59%	41–44, 72, 89–94, 190–208, 223–232, 250–260, 287–297, 302–312, 343–357, 362–370, 399–413
snr_map.py	108	1	99%	152
spatial_resolution.py	249	44	82%	41–43, 47, 68, 153, 212, 338–375
uniformity.py	79	19	76%	47–49, 53, 95–96, 103, 137–152
TOTAL	2878	814	72%