Nimble Digital Imaging for Medicine
All relevant data types including uint16, f16, bf16, complex64 and complex128
Bindings for Python and conversion to NumPy/CuPy/JAX/Torch tensors
# using ssh
git clone git@github.com:StrongCompute/dimble.git
# OR using https
git clone https://github.com/StrongCompute/dimble.git
cd dimble
make install
make validate_install
import dimble
# convert to dimble
dimble.dicom_to_dimble('xray.dicom', 'xray.dimble')
# load a dimble file's pixel data
dataset = dimble.load_dimble('xray.dimble', fields=["7FE00010"], device="cpu")
# load a dimble file's pixel data sliced to a 224x224 chunk offset by 100 in each dimension
dataset = dimble.load_dimble('xray.dimble', fields=["7FE00010"], device="cpu", slices=[slice(100,100+224), slice(100,100+224)])
# convert back to dicom
dimble.dimble_to_dicom("xray.dimble", "xray.dicom")
make install-dev
make install-dev
make test