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Coil options #388

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merged 4 commits into from
Nov 28, 2023
Merged

Coil options #388

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ce15297
Coil options
mollybuckley Oct 19, 2023
b08ca9b
Update snr.py with coil options
mollybuckley Oct 25, 2023
9b8ef3f
Merge branch 'main' into 94-BC-kernel
mollybuckley Oct 26, 2023
2f4293f
Formatting changes
mollybuckley Nov 27, 2023
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6 changes: 3 additions & 3 deletions hazenlib/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -74,7 +74,7 @@

The following Tasks are available:
- ACR phantom:
acr_snr | acr_slice_position | acr_slice_thickness | acr_spatial_resolution | acr_uniformity | acr_ghosting | acr_geometric_accuracy

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- MagNET Test Objects:
snr | snr_map | slice_position | slice_width | spatial_resolution | uniformity | ghosting
- Caliber phantom:
Expand All @@ -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]

Expand All @@ -95,19 +95,18 @@
General Options: available for all Tasks
--report Whether to generate visualisation of the measurement steps.
--output=<path> Provide a folder where report images are to be saved.
--verbose Whether to provide additional metadata about the calculation in the result (slice position and relaxometry tasks)

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--log=<level> Set the level of logging based on severity. Available levels are "debug", "warning", "error", "critical", with "info" as default.

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acr_snr & snr Task options:
--measured_slice_width=<mm> Provide a slice width to be used for SNR measurement, by default it is parsed from the DICOM (optional for acr_snr and snr)

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--subtract=<folder2> Provide a second folder path to calculate SNR by subtraction for the ACR phantom (optional for acr_snr)

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relaxometry Task options:
--calc=<n> Choose 'T1' or 'T2' for relaxometry measurement (required)
--plate_number=<n> Which plate to use for measurement: 4 or 5 (required)
"""


import importlib
import inspect
import logging
Expand Down Expand Up @@ -153,7 +152,7 @@
task = getattr(task_module, selected_task.capitalize())(
input_data=files, report=report, report_dir=report_dir,
**kwargs)
except:

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class_list = [cls.__name__ for _, cls in inspect.getmembers(
sys.modules[task_module.__name__],
lambda x: inspect.isclass(x) and (x.__module__ == task_module.__name__)
Expand Down Expand Up @@ -196,7 +195,8 @@
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'
Expand Down
15 changes: 13 additions & 2 deletions hazenlib/tasks/snr.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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.
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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()
Expand Down Expand Up @@ -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:
Expand Down
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