med-dataloader 0.1.16

A general-purpose Dataloader for Tensorflow 2.x. It supports many medical image formats.

Medical Images Dataloader

A general-purpose Dataloader for Tensorflow 2.x. It supports many medical image formats.

• Free software: MIT license

• Documentation: https://med-dataloader.readthedocs.io.

Features

• TODO

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

History

0.1.16 (2022-06-15)

• Patching is now performed with SAME padding

0.1.15 (2022-05-17)

• img_size support also None value.

0.1.14 (2022-05-16)

• Improved handling of img_size parameters for both 2D and 3D images.

  • User can now declare img_size as a 2- or 3-elements list.

  • Automatic zero-padding or center-based cropping is performed to adapt the size of the image to the declare img_size parameter.

• New features: 3D volumes can be patched into smaller cubic patches. Overlapping between patches is also supported.

0.1.13 (2022-03-10)

• New function: now dataset can be generated also by reading a json file containing list of file paths.

0.1.12 (2021-10-29)

• Fixed minor bug in function norm_with_bounds

0.1.11 (2021-09-10)

• Fixed support for 3D Images

• Fixed minor bugs

0.1.10 (2021-05-11)

• Added support one-hot encoding in case of multi-class label

0.1.9 (2021-05-11)

• Added support for RGB Images

• Fixed some bugs related to norm_bounds types

0.1.8 (2021-05-09)

• Main Changes in the package structure. Now there are two main functions: generate_dataset and get_dataset, both leveraging on DataLoader class.

• The generation of the dataset can be handled also by CLI, to simplify usage.

• Processed data can live by themself. No more need to transfer also original file (e.g. to Drive to make use of them on Colab)

0.1.6 (2021-05-06)

• Improved flexibility for image data types. Now cache dimension reflects the actual dataset dimension.

0.1.5 (2021-04-30)

• Added support for 3D files: now Dataloader automatically detects whether a file is 2D or 3D and returns the properly sized dataset. Please remember that med_dataloader returns tf.data.Dataset object for 2D tasks, 3D is not yet supported.

• Added new notebook in examples folder.

0.1.4 (2021-04-29)

• Improved code flexibility:

  • It is possibile to choose which type of data augmentation is performed

  • Boundaries for data normalization can be set by the user

  • Images can be resized automatically by the user

• Added basic_usage example also as a notebook

0.1.1 (2021-04-20)

• Added code for package

• Basic example of usage inside folder “examples”

• Partial documentation

0.1.0 (2021-04-16)

• First release on PyPI.