Fix broken link in swin-unetr notebook (#1862)

Fixes # .

### Description
A few sentences describing the changes proposed in this pull request.

### Checks
<!--- Put an `x` in all the boxes that apply, and remove the not
applicable items -->
- [ ] Avoid including large-size files in the PR.
- [ ] Clean up long text outputs from code cells in the notebook.
- [ ] For security purposes, please check the contents and remove any
sensitive info such as user names and private key.
- [ ] 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
- [ ] Notebook runs automatically `./runner.sh -t <path to .ipynb file>`

Signed-off-by: YunLiu <[email protected]>

3d_segmentation/swin_unetr_btcv_segmentation_3d.ipynb

@@ -33,7 +33,7 @@
     "\n",
     "For this tutorial, the dataset needs to be downloaded from: https://www.synapse.org/#!Synapse:syn3193805/wiki/217752. More details are provided in the \"Download dataset\" section below.\n",
     "\n",
-    "In addition, the json file for data splits needs to be downloaded from this [link](https://drive.google.com/file/d/1qcGh41p-rI3H_sQ0JwOAhNiQSXriQqGi/view?usp=sharing). Once downloaded, place the json file in the same folder as the dataset. \n",
+    "In addition, the json file for data splits needs to be downloaded from this [link](https://developer.download.nvidia.com/assets/Clara/monai/tutorials/swin_unetr_btcv_dataset_0.json). Once downloaded, place the json file in the same folder as the dataset. \n",
     "\n",
     "For BTCV dataset, under Institutional Review Board (IRB) supervision, 50 abdomen CT scans of were randomly selected from a combination of an ongoing colorectal cancer chemotherapy trial, and a retrospective ventral hernia study. The 50 scans were captured during portal venous contrast phase with variable volume sizes (512 x 512 x 85 - 512 x 512 x 198) and field of views (approx. 280 x 280 x 280 mm3 - 500 x 500 x 650 mm3). The in-plane resolution varies from 0.54 x 0.54 mm2 to 0.98 x 0.98 mm2, while the slice thickness ranges from 2.5 mm to 5.0 mm. \n",
     "\n",
@@ -98,8 +98,6 @@
     "\n",
     "We use weights from self-supervised pre-training of Swin UNETR encoder (3D Swin Tranformer) on a cohort of 5050 CT scans from publicly available datasets. The encoder is pre-trained using reconstructin, rotation prediction and contrastive learning pre-text tasks as shown below. For more details, please refer to [1] (CVPR paper) and see this [repository](https://github.com/Project-MONAI/research-contributions/tree/main/SwinUNETR/Pretrain). \n",
     "\n",
-    "![image](https://lh3.googleusercontent.com/pw/AM-JKLVLgduGZ9naCSasWg09U665NBdd3UD4eLTy15wJiwbmKLS_p5WSZ2MBcRePEJO2tv9X3TkC52MsbnomuPy5JT3vSVeCji1MOEuAzcsxily88TdbHuAt6PzccefwKupbXyOCumK5hzz5Ul38kZnlEQ84=w397-h410-no?authuser=2)\n",
-    "\n",
     "Please download the pre-trained weights from this [link](https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/model_swinvit.pt) and place it in the root directory of this tutorial. \n",
     "\n",
     "If training from scratch is desired, please skip the step for initializing from pre-trained weights. "