Add Montgomery dataset (#249)

Add montgomery dataset

scripts/datasets/medical/check_montgomery.py

@@ -0,0 +1,21 @@
+from torch_em.util.debug import check_loader
+from torch_em.data.datasets.medical import get_montgomery_loader
+
+
+ROOT = "/media/anwai/ANWAI/data/montgomery"
+
+
+def check_montgomery():
+    loader = get_montgomery_loader(
+        path=ROOT,
+        patch_shape=(512, 512),
+        batch_size=2,
+        resize_inputs=True,
+        download=True,
+    )
+
+    check_loader(loader, 8)
+
+
+if __name__ == "__main__":
+    check_montgomery()

torch_em/data/datasets/medical/__init__.py

@@ -3,6 +3,7 @@
 from .busi import get_busi_dataset, get_busi_loader
 from .camus import get_camus_dataset, get_camus_loader
 from .drive import get_drive_dataset, get_drive_loader
+from .montgomery import get_montgomery_dataset, get_montgomery_loader
 from .msd import get_msd_dataset, get_msd_loader
 from .osic_pulmofib import get_osic_pulmofib_dataset, get_osic_pulmofib_loader
 from .papila import get_papila_dataset, get_papila_loader

torch_em/data/datasets/medical/montgomery.py

@@ -0,0 +1,116 @@
+import os
+from glob import glob
+from tqdm import tqdm
+from typing import Union, Tuple
+
+import imageio.v3 as imageio
+
+import torch_em
+
+from .. import util
+
+
+URL = "http://openi.nlm.nih.gov/imgs/collections/NLM-MontgomeryCXRSet.zip"
+CHECKSUM = "54601e952315d8f67383e9202a6e145997ade429f54f7e0af44b4e158714f424"
+
+
+def get_montgomery_data(path, download):
+    os.makedirs(path, exist_ok=True)
+
+    data_dir = os.path.join(path, "MontgomerySet")
+    if os.path.exists(data_dir):
+        return data_dir
+
+    zip_path = os.path.join(path, "NLM-MontgomeryCXRSet.zip")
+    util.download_source(path=zip_path, url=URL, download=download, checksum=CHECKSUM)
+    util.unzip(zip_path=zip_path, dst=path)
+
+    return data_dir
+
+
+def _get_montgomery_paths(path, download):
+    data_dir = get_montgomery_data(path=path, download=download)
+    gt_dir = os.path.join(data_dir, "ManualMask", "gt")
+
+    image_paths = sorted(glob(os.path.join(data_dir, "CXR_png", "*.png")))
+
+    if os.path.exists(gt_dir):
+        gt_paths = sorted(glob(os.path.join(gt_dir, "*.png")))
+        if len(image_paths) == len(gt_paths):
+            return image_paths, gt_paths
+
+    else:
+        os.makedirs(gt_dir, exist_ok=True)
+
+    lmask_dir = os.path.join(data_dir, "ManualMask", "leftMask")
+    rmask_dir = os.path.join(data_dir, "ManualMask", "rightMask")
+    gt_paths = []
+    for image_path in tqdm(image_paths, desc="Merging left and right lung halves"):
+        image_id = os.path.split(image_path)[-1]
+
+        # merge the left and right lung halves into one gt file
+        gt = imageio.imread(os.path.join(lmask_dir, image_id))
+        gt += imageio.imread(os.path.join(rmask_dir, image_id))
+        gt = gt.astype("uint8")
+
+        gt_path = os.path.join(gt_dir, image_id)
+
+        imageio.imwrite(gt_path, gt)
+        gt_paths.append(gt_path)
+
+    return image_paths, gt_paths
+
+
+def get_montgomery_dataset(
+    path: Union[os.PathLike, str],
+    patch_shape: Tuple[int, int],
+    resize_inputs: bool = True,
+    download: bool = False,
+    **kwargs
+):
+    """Dataset for the segmentation of lungs in x-ray.
+
+    This dataset is from the publication:
+    - https://doi.org/10.1109/TMI.2013.2284099
+    - https://doi.org/10.1109/tmi.2013.2290491
+
+    The database is located at
+    https://data.lhncbc.nlm.nih.gov/public/Tuberculosis-Chest-X-ray-Datasets/Montgomery-County-CXR-Set/MontgomerySet/index.html.
+
+    Please cite it if you use this dataset for a publication.
+    """
+    image_paths, gt_paths = _get_montgomery_paths(path=path, download=download)
+
+    if resize_inputs:
+        resize_kwargs = {"patch_shape": patch_shape, "is_rgb": False}
+        kwargs, patch_shape = util.update_kwargs_for_resize_trafo(
+            kwargs=kwargs, patch_shape=patch_shape, resize_inputs=resize_inputs, resize_kwargs=resize_kwargs
+        )
+
+    dataset = torch_em.default_segmentation_dataset(
+        raw_paths=image_paths,
+        raw_key=None,
+        label_paths=gt_paths,
+        label_key=None,
+        patch_shape=patch_shape,
+        **kwargs
+    )
+    return dataset
+
+
+def get_montgomery_loader(
+    path: Union[os.PathLike, str],
+    patch_shape: Tuple[int, int],
+    batch_size: int,
+    resize_inputs: bool = True,
+    download: bool = False,
+    **kwargs
+):
+    """Dataloader for the segmentation of lungs in x-ray. See 'get_montgomery_dataset' for details.
+    """
+    ds_kwargs, loader_kwargs = util.split_kwargs(torch_em.default_segmentation_dataset, **kwargs)
+    dataset = get_montgomery_dataset(
+        path=path, patch_shape=patch_shape, resize_inputs=resize_inputs, download=download, **ds_kwargs
+    )
+    loader = torch_em.get_data_loader(dataset=dataset, batch_size=batch_size, **loader_kwargs)
+    return loader