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>

Author: 4 people

README.md

@@ -331,6 +331,8 @@ Illustrate reading NIfTI files and iterating over image patches of the volumes l
 This tutorial illustrates the flexible network APIs and utilities.
 ##### [postprocessing_transforms](./modules/postprocessing_transforms.ipynb)
 This notebook shows the usage of several postprocessing transforms based on the model output of spleen segmentation task.
+##### [idc_dataset](./modules/idc_dataset.ipynb)
+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.
 ##### [public_datasets](./modules/public_datasets.ipynb)
 This notebook shows how to quickly set up training workflow based on `MedNISTDataset` and `DecathlonDataset`, and how to create a new dataset.
 ##### [tcia_csv_processing](./modules/tcia_csv_processing.ipynb)
@@ -386,4 +388,3 @@ Example shows the use cases of using MONAI to evaluate the performance of a gene
 
 #### [VISTA2D](./vista_2d)
 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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