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Commit 7bedfd0

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fedorovpre-commit-ci[bot]claudeericspod
authored
enh: add notebook demonstrating access to data from Imaging Data Commons (#2063)
### Description This notebook demonstrates how to load images and segmentations from [Imaging Data Commons](https://portal.imaging.datacommons.cancer.gov/explore/). ### Checks <!--- Put an `x` in all the boxes that apply, and remove the not applicable items --> - [x] Avoid including large-size files in the PR. - [x] Clean up long text outputs from code cells in the notebook. - [x] For security purposes, please check the contents and remove any sensitive info such as user names and private key. - [x] Ensure (1) hyperlinks and markdown anchors are working (2) use relative paths for tutorial repo files (3) put figure and graphs in the `./figure` folder - [x] Notebook runs automatically `./runner.sh -t <path to .ipynb file>` <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **Documentation** * Added a tutorial notebook showing how to query/download IDC cancer imaging data and load DICOM images and segmentations into MONAI; removed a stray non‑ASCII line in the docs. * **Chores** * Updated CI rules to skip executing the new tutorial notebook during automated runs to avoid long or incompatible executions. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Signed-off-by: Andrey Fedorov <andrey.fedorov@gmail.com> Signed-off-by: Andrey Fedorov <fedorov@bwh.harvard.edu> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> Co-authored-by: Eric Kerfoot <17726042+ericspod@users.noreply.github.com>
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‎README.md‎

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@@ -331,6 +331,8 @@ Illustrate reading NIfTI files and iterating over image patches of the volumes l
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This tutorial illustrates the flexible network APIs and utilities.
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##### [postprocessing_transforms](./modules/postprocessing_transforms.ipynb)
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This notebook shows the usage of several postprocessing transforms based on the model output of spleen segmentation task.
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##### [idc_dataset](./modules/idc_dataset.ipynb)
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This notebook shows how to query and download public cancer imaging data from NCI Imaging Data Commons (IDC) using `idc-index`, and how to load DICOM images and DICOM-SEG segmentations into MONAI for AI/ML preprocessing.
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##### [public_datasets](./modules/public_datasets.ipynb)
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This notebook shows how to quickly set up training workflow based on `MedNISTDataset` and `DecathlonDataset`, and how to create a new dataset.
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##### [tcia_csv_processing](./modules/tcia_csv_processing.ipynb)
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#### [VISTA2D](./vista_2d)
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This tutorial demonstrates how to train a cell segmentation model using the [MONAI](https://monai.io/) framework and the [Segment Anything Model (SAM)](https://github.com/facebookresearch/segment-anything) on the [Cellpose dataset](https://www.cellpose.org/).
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