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Merged
wyli merged 6 commits into from
Apr 2, 2022
Merged

Add support for level in PatchWSIDataset #4036

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f960c68
Add support for level as input
bhashemian Mar 31, 2022
aaa9194
Add unittests for levels
bhashemian Mar 31, 2022
e119c38
Update docstring
bhashemian Mar 31, 2022
bd26c0b
Merge branch 'dev' into fix_4034
bhashemian Apr 2, 2022
5577d80
Add kwargs for WSIReader in all datasets
bhashemian Apr 2, 2022
1d9b7b2
Update docstring
bhashemian Apr 2, 2022
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17 changes: 12 additions & 5 deletions monai/apps/pathology/data/datasets.py
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Original file line number Diff line number Diff line change
Expand Up @@ -35,6 +35,7 @@ class PatchWSIDataset(Dataset):
transform: transforms to be executed on input data.
image_reader_name: the name of library to be used for loading whole slide imaging, either CuCIM or OpenSlide.
Defaults to CuCIM.
kwargs: additional parameters for ``WSIReader``

Note:
The input data has the following form as an example:
Expand All @@ -56,6 +57,7 @@ def __init__(
patch_size: Union[int, Tuple[int, int]],
transform: Optional[Callable] = None,
image_reader_name: str = "cuCIM",
**kwargs,
):
super().__init__(data, transform)

Expand All @@ -65,7 +67,7 @@ def __init__(

self.image_path_list = list({x["image"] for x in self.data})
self.image_reader_name = image_reader_name.lower()
self.image_reader = WSIReader(image_reader_name)
self.image_reader = WSIReader(backend=image_reader_name, **kwargs)
self.wsi_object_dict = None
if self.image_reader_name != "openslide":
# OpenSlide causes memory issue if we prefetch image objects
Expand Down Expand Up @@ -119,17 +121,18 @@ class SmartCachePatchWSIDataset(SmartCacheDataset):
will take the minimum of (cache_num, data_length x cache_rate, data_length).
num_init_workers: the number of worker threads to initialize the cache for first epoch.
If num_init_workers is None then the number returned by os.cpu_count() is used.
If a value less than 1 is speficied, 1 will be used instead.
If a value less than 1 is specified, 1 will be used instead.
num_replace_workers: the number of worker threads to prepare the replacement cache for every epoch.
If num_replace_workers is None then the number returned by os.cpu_count() is used.
If a value less than 1 is speficied, 1 will be used instead.
If a value less than 1 is specified, 1 will be used instead.
progress: whether to display a progress bar when caching for the first epoch.
copy_cache: whether to `deepcopy` the cache content before applying the random transforms,
default to `True`. if the random transforms don't modify the cache content
or every cache item is only used once in a `multi-processing` environment,
may set `copy=False` for better performance.
as_contiguous: whether to convert the cached NumPy array or PyTorch tensor to be contiguous.
it may help improve the performance of following logic.
kwargs: additional parameters for ``WSIReader``

"""

Expand All @@ -149,13 +152,15 @@ def __init__(
progress: bool = True,
copy_cache: bool = True,
as_contiguous: bool = True,
**kwargs,
):
patch_wsi_dataset = PatchWSIDataset(
data=data,
region_size=region_size,
grid_shape=grid_shape,
patch_size=patch_size,
image_reader_name=image_reader_name,
**kwargs,
)
super().__init__(
data=patch_wsi_dataset, # type: ignore
Expand Down Expand Up @@ -183,7 +188,8 @@ class MaskedInferenceWSIDataset(Dataset):
patch_size: the size of patches to be extracted from the whole slide image for inference.
transform: transforms to be executed on extracted patches.
image_reader_name: the name of library to be used for loading whole slide imaging, either CuCIM or OpenSlide.
Defaults to CuCIM.
Defaults to CuCIM.
kwargs: additional parameters for ``WSIReader``

Note:
The resulting output (probability maps) after performing inference using this dataset is
Expand All @@ -196,14 +202,15 @@ def __init__(
patch_size: Union[int, Tuple[int, int]],
transform: Optional[Callable] = None,
image_reader_name: str = "cuCIM",
**kwargs,
) -> None:
super().__init__(data, transform)

self.patch_size = ensure_tuple_rep(patch_size, 2)

# set up whole slide image reader
self.image_reader_name = image_reader_name.lower()
self.image_reader = WSIReader(image_reader_name)
self.image_reader = WSIReader(backend=image_reader_name, **kwargs)

# process data and create a list of dictionaries containing all required data and metadata
self.data = self._prepare_data(data)
Expand Down
120 changes: 118 additions & 2 deletions tests/test_patch_wsi_dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,6 +41,31 @@
[{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[1]]])}],
]

TEST_CASE_0_L1 = [
{
"data": [{"image": FILE_PATH, "location": [0, 0], "label": [1]}],
"region_size": (1, 1),
"grid_shape": (1, 1),
"patch_size": 1,
"level": 1,
"image_reader_name": "cuCIM",
},
[{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[1]]])}],
]

TEST_CASE_0_L2 = [
{
"data": [{"image": FILE_PATH, "location": [0, 0], "label": [1]}],
"region_size": (1, 1),
"grid_shape": (1, 1),
"patch_size": 1,
"level": 1,
"image_reader_name": "cuCIM",
},
[{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[1]]])}],
]


TEST_CASE_1 = [
{
"data": [{"image": FILE_PATH, "location": [10004, 20004], "label": [0, 0, 0, 1]}],
Expand All @@ -57,6 +82,41 @@
],
]


TEST_CASE_1_L0 = [
{
"data": [{"image": FILE_PATH, "location": [10004, 20004], "label": [0, 0, 0, 1]}],
"region_size": (8, 8),
"grid_shape": (2, 2),
"patch_size": 1,
"level": 0,
"image_reader_name": "cuCIM",
},
[
{"image": np.array([[[247]], [[245]], [[248]]], dtype=np.uint8), "label": np.array([[[0]]])},
{"image": np.array([[[245]], [[247]], [[244]]], dtype=np.uint8), "label": np.array([[[0]]])},
{"image": np.array([[[246]], [[246]], [[246]]], dtype=np.uint8), "label": np.array([[[0]]])},
{"image": np.array([[[246]], [[246]], [[246]]], dtype=np.uint8), "label": np.array([[[1]]])},
],
]


TEST_CASE_1_L1 = [
{
"data": [{"image": FILE_PATH, "location": [10004, 20004], "label": [0, 0, 0, 1]}],
"region_size": (8, 8),
"grid_shape": (2, 2),
"patch_size": 1,
"level": 1,
"image_reader_name": "cuCIM",
},
[
{"image": np.array([[[248]], [[246]], [[249]]], dtype=np.uint8), "label": np.array([[[0]]])},
{"image": np.array([[[196]], [[187]], [[192]]], dtype=np.uint8), "label": np.array([[[0]]])},
{"image": np.array([[[245]], [[243]], [[244]]], dtype=np.uint8), "label": np.array([[[0]]])},
{"image": np.array([[[246]], [[242]], [[243]]], dtype=np.uint8), "label": np.array([[[1]]])},
],
]
TEST_CASE_2 = [
{
"data": [{"image": FILE_PATH, "location": [0, 0], "label": [1]}],
Expand Down Expand Up @@ -90,6 +150,43 @@
[{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[1]]])}],
]

TEST_CASE_OPENSLIDE_0_L0 = [
{
"data": [{"image": FILE_PATH, "location": [0, 0], "label": [1]}],
"region_size": (1, 1),
"grid_shape": (1, 1),
"patch_size": 1,
"level": 0,
"image_reader_name": "OpenSlide",
},
[{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[1]]])}],
]

TEST_CASE_OPENSLIDE_0_L1 = [
{
"data": [{"image": FILE_PATH, "location": [0, 0], "label": [1]}],
"region_size": (1, 1),
"grid_shape": (1, 1),
"patch_size": 1,
"level": 1,
"image_reader_name": "OpenSlide",
},
[{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[1]]])}],
]


TEST_CASE_OPENSLIDE_0_L2 = [
{
"data": [{"image": FILE_PATH, "location": [0, 0], "label": [1]}],
"region_size": (1, 1),
"grid_shape": (1, 1),
"patch_size": 1,
"level": 2,
"image_reader_name": "OpenSlide",
},
[{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[1]]])}],
]

TEST_CASE_OPENSLIDE_1 = [
{
"data": [{"image": FILE_PATH, "location": [10004, 20004], "label": [0, 0, 0, 1]}],
Expand All @@ -113,7 +210,18 @@ def setUp(self):
hash_val = testing_data_config("images", FILE_KEY, "hash_val")
download_url_or_skip_test(FILE_URL, FILE_PATH, hash_type=hash_type, hash_val=hash_val)

@parameterized.expand([TEST_CASE_0, TEST_CASE_1, TEST_CASE_2, TEST_CASE_3])
@parameterized.expand(
[
TEST_CASE_0,
TEST_CASE_0_L1,
TEST_CASE_0_L2,
TEST_CASE_1,
TEST_CASE_1_L0,
TEST_CASE_1_L1,
TEST_CASE_2,
TEST_CASE_3,
]
)
@skipUnless(has_cim, "Requires CuCIM")
def test_read_patches_cucim(self, input_parameters, expected):
dataset = PatchWSIDataset(**input_parameters)
Expand All @@ -124,7 +232,15 @@ def test_read_patches_cucim(self, input_parameters, expected):
self.assertIsNone(assert_array_equal(samples[i]["label"], expected[i]["label"]))
self.assertIsNone(assert_array_equal(samples[i]["image"], expected[i]["image"]))

@parameterized.expand([TEST_CASE_OPENSLIDE_0, TEST_CASE_OPENSLIDE_1])
@parameterized.expand(
[
TEST_CASE_OPENSLIDE_0,
TEST_CASE_OPENSLIDE_0_L0,
TEST_CASE_OPENSLIDE_0_L1,
TEST_CASE_OPENSLIDE_0_L2,
TEST_CASE_OPENSLIDE_1,
]
)
@skipUnless(has_osl, "Requires OpenSlide")
def test_read_patches_openslide(self, input_parameters, expected):
dataset = PatchWSIDataset(**input_parameters)
Expand Down