Merged in feature/RAM-4285-acr-mri-mtf (pull request #495)

RAM-4285 Add 10-90% MTF for ACR MRI phantom

Approved-by: Randy Taylor

docs/source/acr.rst

@@ -461,6 +461,8 @@ Interpreting MRI Results
         * ``measured_slice_thickness_mm``: The measured slice thickness in mm.
         * ``row_mtf_50``: The MTF at 50% for the row-based ROIs.
         * ``col_mtf_50``: The MTF at 50% for the column-based ROIs.
+        * ``row_mtf_lp_mm``: The MTF:lp/mm for the row-based ROIs from 10-90% in 10% increments.
+        * ``col_mtf_lp_mm``: The MTF:lp/mm for the column-based ROIs from 10-90% in 10% increments.
         * ``rois``: A dictionary of the analyzed MTF ROIs. The key is the name of the
           ROI; e.g. ``Row 1.1`` and the key is a dictionary of the following items:
 

docs/source/changelog.rst

@@ -19,6 +19,8 @@ ACR MRI
 * :bdg-warning:`Fixed` The positive and negative diagonal geometric distortion calculations (``results_data().geometric_distortion_module.profiles["negative diagonal"]['width (mm)']``) for the ACR Large MRI phantom were not scaled correctly.
   Since the pixel distance is diagonal the physical spacing between pixels is actually :math:`\sqrt{2}` times the pixel spacing.
   This is now fixed. Prior values can be scaled by :math:`\sqrt{2}` to get the correct values.
+* :bdg-success:`Feature` MTF is now provided in 10% increments from 10-90% in the ``results_data`` return object
+   for both row and column MTFs as ``row_mtf_lp_mm`` and ``col_mtf_lp_mm``. This is to match CT-like MTF outputs.
 
 v 3.30.0
 --------

pylinac/acr.py

@@ -912,6 +912,14 @@ class MRSlice1ModuleOutput(BaseModel):
         description="The MTF at 50% for the column-based ROIs.",
         title="Column-wise 50% MTF (lp/mm)",
     )
+    row_mtf_lp_mm: dict[int, float] = Field(
+        description="A key-value pair of the MTF. The key is the relative resolution in % and the value is the lp/mm at that resolution",
+        title="MTF (lp/mm)",
+    )
+    col_mtf_lp_mm: dict[int, float] = Field(
+        description="A key-value pair of the MTF. The key is the relative resolution in % and the value is the lp/mm at that resolution",
+        title="MTF (lp/mm)",
+    )
 
 
 class MRUniformityModule(CatPhanModule):
@@ -1636,6 +1644,15 @@ def results(self, as_str: bool = True) -> str | tuple:
             return string
 
     def _generate_results_data(self) -> ACRMRIResult:
+        resolutions = range(10, 91, 10)  # 10-90% in 10% increments
+        row_mtfs = {
+            resolution: self.slice1.row_mtf.relative_resolution(resolution)
+            for resolution in resolutions
+        }
+        col_mtfs = {
+            resolution: self.slice1.col_mtf.relative_resolution(resolution)
+            for resolution in resolutions
+        }
         return ACRMRIResult(
             phantom_model=self._model,
             phantom_roll_deg=self.catphan_roll,
@@ -1650,6 +1667,8 @@ def _generate_results_data(self) -> ACRMRIResult:
                 measured_slice_thickness_mm=self.slice1.measured_slice_thickness_mm,
                 row_mtf_50=self.slice1.row_mtf.relative_resolution(50),
                 col_mtf_50=self.slice1.col_mtf.relative_resolution(50),
+                row_mtf_lp_mm=row_mtfs,
+                col_mtf_lp_mm=col_mtfs,
             ),
             slice11=MRSlice11ModuleOutput(
                 offset=MR_SLICE11_MODULE_OFFSET_MM,

tests_basic/test_acr.py

@@ -338,6 +338,18 @@ def construct_analyzed_instance(self):
         mri.analyze()
         return mri
 
+    def test_row_mtf_keys(self):
+        phantom = self.construct_analyzed_instance()
+        data = phantom.results_data()
+        for key, value in {10: 1.13, 80: 0.564}.items():
+            self.assertAlmostEqual(data.slice1.row_mtf_lp_mm[key], value, delta=0.01)
+
+    def test_col_mtf_keys(self):
+        phantom = self.construct_analyzed_instance()
+        data = phantom.results_data()
+        for key, value in {10: 1.11, 80: 0.826}.items():
+            self.assertAlmostEqual(data.slice1.col_mtf_lp_mm[key], value, delta=0.01)
+
 
 class TestMRGeneral(TestCase):
     def setUp(self):