New loader: Load PNG/TIF/JPG microscopy files as Nibabel objects (#813)

* Remove apply_canonical function, revert to nib.as_closest_canonical

* Remove get_voxel_size, revert to header.get_zooms

* Remove get_shape, revert to header.get_data_shape

* Remove get_data, revert to nibabel get_fdata

* In read_file, convert png/tif/jpg to Nifti1Image object

* Get pixel size from json metadata and set zooms in nifti header

* loader/utils.py: Correction to filtering of extensions in bids_dataframe
(was not filtering derivatives extensions before)

* Update read_file in SegmentationPair to convert PNG to Nibabel object
and write Nifti file

* configuration_file.rst: Update extensions definition and example

* Move file extension check from SegmentationPair to get_file_extension in
loader/utils.py

* Add update_filename_to_nifti function to loader/utils.py

* test_loader.py: update test_load_dataset_2d_png

* testing.py: Check extentions and update paths if not NifTI in get_gt

* evaluation.py: Check extentions and update paths if not NifTI in
evaluate

* inference.py: Check extentions and update paths if not NifTI in
pred_to_nib

* Add TODO comment for inference in main.py

* Add .tif and .tiff microscopy extensions to bids_dataframe

* loader/utils.py: Correction to update_filename_to_nifti

* Update config_new_loader.json to test the PR

* Set self.extensions to nii and nii.gz by default in BidsDataframe when
no extensions are provided in config

* Update docs/source/configuration_file.rst

Co-authored-by: Joshua Newton <joshuacwnewton@gmail.com>

* Move file extension validation to read_file in SegmentationPair

* Use update_filename_to_nifti to update path in read_file

* Remove if self.extensions condition in filtering of bids_dataframe
(always true)

* Correction to PixelSize assignment and comments

* Add convert_file_to_nifti method to SegmentationPair

* Update update_filename_to_nifti docstings

Co-authored-by: Joshua Newton <joshuacwnewton@gmail.com>

* Update read_file docstrings

* Add list of supported file extensions in error message in read_file

* Fix resize of PixelSize

Co-authored-by: Joshua Newton <joshuacwnewton@gmail.com>

docs/source/configuration_file.rst

@@ -287,7 +287,7 @@ will be randomly chosen.
         "$schema": "http://json-schema.org/draft-04/schema#",
         "title": "extensions",
         "description": "Used to specify a list of file extensions to be selected for
-            training/testing.",
+            training/testing. If not specified, then `.nii` and `.nii.gz` will be used by default.",
         "type": "list, string"
     }
 
@@ -297,7 +297,7 @@ will be randomly chosen.
 
     {
         "loader_parameters": {
-            "extensions": [".nii.gz"]
+            "extensions": [".png"]
         }
     }
 

ivadomed/config/config_new_loader.json

@@ -9,18 +9,18 @@
         "safety_factor": [1.0, 1.0, 1.0]
     },
     "loader_parameters": {
-        "path_data": ["data_example_spinegeneric"],
+        "path_data": ["data_example_microscopy_sem"],
         "bids_config": "ivadomed/config/config_bids.json",
         "subject_selection": {"n": [], "metadata": [], "value": []},
-        "target_suffix": ["_seg-manual"],
-        "extensions": [],
+        "target_suffix": ["_seg-axon-manual", "_seg-myelin-manual"],
+        "extensions": [".png"],
         "roi_params": {
             "suffix": null,
             "slice_filter_roi": null
         },
         "contrast_params": {
-            "training_validation": ["T2w"],
-            "testing": ["T2w"],
+            "training_validation": ["SEM"],
+            "testing": ["SEM"],
             "balance": {}
         },
         "slice_filter_params": {
@@ -34,19 +34,19 @@
     "split_dataset": {
         "fname_split": null,
         "random_seed": 6,
-        "split_method" : "participant_id",
+        "split_method" : "sample_id",
         "data_testing": {"data_type": null, "data_value":[]},
         "balance": null,
-        "train_fraction": 0.1,
-        "test_fraction": 0.8
+        "train_fraction": 0.2,
+        "test_fraction": 0.2
     },
     "training_parameters": {
         "batch_size": 18,
         "loss": {
             "name": "DiceLoss"
         },
         "training_time": {
-            "num_epochs": 1,
+            "num_epochs": 5,
             "early_stopping_patience": 50,
             "early_stopping_epsilon": 0.001
         },
@@ -75,8 +75,8 @@
         "bn_momentum": 0.1,
         "final_activation": "sigmoid",
         "depth": 3,
-        "length_2D": [50, 50],
-        "stride_2D": [45, 45]
+        "length_2D": [],
+        "stride_2D": []
     },
     "FiLMedUnet": {
         "applied": false,
@@ -85,7 +85,8 @@
     },
     "transformation": {
       "CenterCrop": {
-            "size": [128, 128]},
+            "size": [256, 256]
+      },
       "NumpyToTensor": {},
       "NormalizeInstance": {"applied_to": ["im"]}
     }

ivadomed/evaluation.py

@@ -9,6 +9,7 @@
 
 from ivadomed import metrics as imed_metrics
 from ivadomed import postprocessing as imed_postpro
+from ivadomed.loader import utils as imed_loader_utils
 
 # labels of paint_objects method
 TP_COLOUR = 1
@@ -52,6 +53,9 @@ def evaluate(bids_df, path_output, target_suffix, eval_params):
         fname_gt = bids_df.df[bids_df.df['filename']
                           .str.contains('|'.join(bids_df.get_derivatives(subj_acq, all_deriv)))]['path'].to_list()
 
+        # Check fname_gt extentions and update paths if not NifTI
+        fname_gt = [imed_loader_utils.update_filename_to_nifti(fname) for fname in fname_gt]
+
         # Uncertainty
         data_uncertainty = None
 

ivadomed/inference.py

@@ -136,6 +136,10 @@ def pred_to_nib(data_lst: List[np.ndarray], z_lst: List[int], fname_ref: str, fn
     Returns:
         nibabel.Nifti1Image: NiBabel object containing the Network prediction.
     """
+
+    # Check fname_ref extention and update path if not NifTI
+    fname_ref = imed_loader_utils.update_filename_to_nifti(fname_ref)
+
     # Load reference nibabel object
     nib_ref = nib.load(fname_ref)
     nib_ref_can = nib.as_closest_canonical(nib_ref)
@@ -192,7 +196,7 @@ def pred_to_nib(data_lst: List[np.ndarray], z_lst: List[int], fname_ref: str, fn
         affine=None,
         header=nib_ref.header.copy()
     )
-    # save as nifti file
+    # save as NifTI file
     if fname_out is not None:
         nib.save(nib_pred, fname_out)
 
@@ -341,6 +345,7 @@ def segment_volume(folder_model: str, fname_images: list, gpu_id: int = 0, optio
         logger.warning("fname_roi has not been specified, then the entire volume is processed.")
         loader_params["slice_filter_params"]["filter_empty_mask"] = False
 
+    # TODO: Add PixelSize from options to filename_pairs metadata for microscopy inference (issue #306)
     filename_pairs = [(fname_images, None, fname_roi, metadata if isinstance(metadata, list) else [metadata])]
 
     kernel_3D = bool('Modified3DUNet' in context and context['Modified3DUNet']['applied']) or \