brainweb - BrainWeb-based multimodal models v1.6.0

• fix get_mmr_fromfile arguments being ignored (#5 <- #3)
• fix toPetMmr ignoring modes (#7)
• cache & make configurable: resolution & PET activity class (#8, #6 <- #4)
• add `getlabelprobabilities() (#8 <- #2)
  • add Act.all_labels
  • expose Act
• add trim_zeros_ROI()
• make toPetMmr() return ndarray
• update example images
• update dependencies

- Python
Published by casperdcl over 5 years ago

brainweb - BrainWeb-based multimodal models v1.5.2

• suppress volshow tight layout warning
• misc minor framework updates

- Python
Published by casperdcl over 5 years ago

brainweb - BrainWeb-based multimodal models v1.5.1

• fix PET/mu map intensities
• update documentation
• add pip install brainweb[register] convenience

- Python
Published by casperdcl almost 6 years ago

brainweb - BrainWeb-based multimodal models v1.5.0

• add register
• fix python3
• update documentation

- Python
Published by casperdcl about 6 years ago

brainweb - BrainWeb-based multimodal models v1.4.0

• auto-clear unused axes
• add Amyloid
• expose PetClass and other intensities
• minor documentation update

- Python
Published by casperdcl over 6 years ago

brainweb - BrainWeb-based multimodal models v1.3.0

• volshow updates
  • allow repeat tight_layout
  • fontproperties
  • frameon=False (fully borderless)
• executable setup.py

- Python
Published by casperdcl over 6 years ago

brainweb - BrainWeb-based multimodal models v1.2.0

• update documentation
• add volshow():vmins, vmaxs, tight_layout

- Python
Published by casperdcl over 6 years ago

brainweb - BrainWeb-based multimodal models v1.1.0

• expose get_files():progress=True
• add CI testing (travis)
  • add flake8
  • add setup.py check
• move to setup.cfg
• add & update badges

- Python
Published by casperdcl almost 7 years ago

brainweb - BrainWeb-based multimodal models v1.0.0

Beta release

Features

• Caches data to ~/.brainweb/
  • raw data source http://brainweb.bic.mni.mcgill.ca/brainweb/anatomic_normal_20.html uint16(362, 434, 362)
• Transforms to Siemens Biograph mMR volume dimensions float32(127, 344, 344)
• Modifies to have FDG, T1, T2 and attenuation map intensities
• Adds non-piecewise-constant randomised structure for more realistic ground truths
• Adds lesions
• Flexible multi-volume slicing tool for Jupyter notebooks brainweb.volshow

- Python
Published by casperdcl almost 7 years ago