Merge branch 'main' of https://huggingface.co/datasets/LMUK-RADONC-PHYS-RES/TrackRAD2025

README.md

@@ -1,19 +1,20 @@
 ---
 license: cc-by-nc-4.0
+size_categories:
+- 1M<n<10M
+task_categories:
+- image-segmentation
+- mask-generation
 tags:
 - lesion-segmentation
 - lesion-tracking
 - real-time
 - cine-MRI
 - radiotherapy
-task_categories:
-- image-segmentation
-- mask-generation
-size_categories:
-- 1M<n<10M
 challenge_homepage: https://trackrad2025.grand-challenge.org/trackrad2025/
 challenge_repository: https://github.com/LMUK-RADONC-PHYS-RES/trackrad2025/
 ---
+
 ### **The dataset 🗃️**
 Overall, the TrackRAD2025 challenge provides over **2.8 million unlabeled** sagittal cine-MRI frames from 477 individual patients, and over **10,000 labeled** sagittal cine-MRI frames 
 (+8000 from frames with multiple observers) from 108 individual patients. Precisely,
@@ -24,7 +25,7 @@ The **training set**, which comprises the 477 unlabeled cases plus 50 labeled ca
 Participants can further subdivide this dataset locally into training and validation. The remaining 58 labeled cases building the **preliminary and final testing set** is only 
 accessible for evaluation via submission to the challenge. A couple of years after the challenge is closed, the testing set data is also going to be uploaded to the same location as the training set.
 
-Detailed information about the dataset are provided in the following paper "<u>link data paper (expected early 2025)</u>".
+Detailed information about the dataset are provided in the preprint https://arxiv.org/abs/2503.19119 under revision in Medical Physics.
 
 The challenge website can be found here: https://trackrad2025.grand-challenge.org/trackrad2025/
 
@@ -194,4 +195,4 @@ The following pre-processing steps were performed on the data:
 - Anonymization
 - Reshaping and orientation correction
 - Resampling to 1x1 mm2 in-plane pixel spacing
-- Conversion to 16-bit unsigned integer
+- Conversion to 16-bit unsigned integer