HandBones (hand radiographs with per-bone masks)
Part of the FleXray data release. Repackaged from the original distribution at https://universe.roboflow.com/boneage-x90qt/-hand-bones-mdjkr under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
Citation: Roboflow Universe project boneage-x90qt/-hand-bones-mdjkr (uploader-declared CC BY 4.0).
Contents
- 93 samples (test: 13, train: 65, val: 15); 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: carpals - channel
2: phalange_distal - channel
3: phalange_intermediate - channel
4: metacarpals - channel
5: phalange_proximal - channel
6: radii - channel
7: 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/HandBones