ElbowLat (lateral elbow radiographs)
Part of the FleXray data release. Repackaged from the original distribution at https://universe.roboflow.com/ionspace/elbow_lat-lnn0s-pmycd under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
Citation: Roboflow Universe project ionspace/elbow_lat-lnn0s-pmycd (CC BY 4.0).
Contents
- 601 samples (test: 91, train: 419, val: 91); one image and one label per sample.
images/*.png: 16-bit grayscale PNG, intensities in [0, 65535] map linearly to [0, 1].labels/: binary channel masks (NPY, C x H x W). Label ids/channels:- channel
0: background - channel
1: humeri - channel
2: radii - channel
3: ulnae dataset.yml:fxr-datasetmanifest (schema version 1). Splits are the ones used in the FleXray paper;metadata.original_shapeis the source image shape.
Preprocessing
Every image was min-max normalized to [0, 1] per image, padded to a square with zeros (centered) and resized to 256 x 256 (area interpolation for images, nearest for labels). Labels were remapped from the source annotation to the dataset-native names listed above; the FleXray package maps those names into its label protocol at training time.
Usage
python -m pip install "flexray[train]"
fxr-dataset validate dataset.yml
fxr-dataset pack dataset.yml /data/flexray/ElbowLat