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A collection of pre-built dataset classes for medical datasets.

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Medaset

A collection of pre-built dataset classes for MEDical datASETs.

python monai-shieldio pytorch Code style: black

Objectives

  • Compatible to PyTorch and MONAI
  • Providing some off-the-shelf features to the Dataset class, including but not limited to, dataset extracting, loading and visualization.

Getting started

git clone this repo and install it using

pip install -e .

Caution

Naming convention changed!! For the sake of readibility, only the first letters in each acronym are now capitalized.

Currently Supported Datasets

  • AMOS (Abdominal Multi-Organ Segmentation)
    [Grand Challenge] [Arxiv]
    • AMOS provides 500 CT and 100 MRI scans collected from multi-center, multi-vendor, multi-modality, multi-phase, multi-disease patients, each with voxel-level annotations of 15 abdominal organs.
    • Structure: spleen, right kidney, left kidney, gallbladder, esophagus, liver, stomach, aorta, inferior vena cava, pancreas, right adrenal gland, left adrenal gland, duodenum, bladder, prostate/uterus.
    • Dataset classes: AmosDataset, SimpleAmosDataset

  • CHAOS (Combined (CT-MR) Healthy Abdominal Organ Segmentation)
    [Grand Challenge] [Arxiv]
    • The CHAOS challenge data contains 40 CT scans and 40 MR scans of upper abdomen area.
    • Structure (Modality): Liver (CT/MR), Kidneys (MR), Spleen (MR)
    • Dataset classes: ChaosCtDataset, ChaosT2spirDataset (The T1-DUAL sequence is not supported currently)

  • SMAT (Skeletal Muscle and Adipose Tissue)
    • Private dataset
    • Dataset classes: SmatCtDataset, SmatMrDataset, SmatDataset

Useful Links

Metadata Desciptions

Medical Image Coordinate Systems

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A collection of pre-built dataset classes for medical datasets.

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