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challenge_homepage: https://trackrad2025.grand-challenge.org/trackrad2025/
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challenge_repository: https://github.com/LMUK-RADONC-PHYS-RES/trackrad2025/
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Overall, the TrackRAD2025 challenge will have over <u>2.5 million</u> unlabelled sagittal cine-MRI frames from 500 individual patients, and over 10,000 labelled sagittal cine-MRI frames (+8000 from frames with multiple observers) from 110 individual patients. Precisely,
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a cohort of <u>500</u> unlabeled and <u>110</u> manually labeled patients has been prepared for participants. For each patient, 2D sagittal cine MRI data (time-resolved sequence of 2D images) has been acquired during the course of radiotherapy treatments at 0.35 T (ViewRay MRIdian) or 1.5 T (Elekta Unity) MRI-linacs from six international centers. Tracking targets (typically tumors) in the thorax, abdomen and pelvis were included as these can be affected by motion and reflect the most often treated anatomies on MRI-linacs. The <u>training set</u>, which comprises the <u>500</u> unlabeled cases plus <u>50</u> labeled cases was publicly released. Participants can further subdivide this dataset locally into training and validation. The remaining <u>60</u> labeled cases building the <u>preliminary and final testing set</u> is only accessible for evaluation via submission to the challenge.
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challenge_homepage: https://trackrad2025.grand-challenge.org/trackrad2025/
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challenge_repository: https://github.com/LMUK-RADONC-PHYS-RES/trackrad2025/
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## **The dataset 🗃️**
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Overall, the TrackRAD2025 challenge will have over <u>2.5 million</u> unlabelled sagittal cine-MRI frames from 500 individual patients, and over 10,000 labelled sagittal cine-MRI frames (+8000 from frames with multiple observers) from 110 individual patients. Precisely,
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a cohort of <u>500</u> unlabeled and <u>110</u> manually labeled patients has been prepared for participants. For each patient, 2D sagittal cine MRI data (time-resolved sequence of 2D images) has been acquired during the course of radiotherapy treatments at 0.35 T (ViewRay MRIdian) or 1.5 T (Elekta Unity) MRI-linacs from six international centers. Tracking targets (typically tumors) in the thorax, abdomen and pelvis were included as these can be affected by motion and reflect the most often treated anatomies on MRI-linacs. The <u>training set</u>, which comprises the <u>500</u> unlabeled cases plus <u>50</u> labeled cases was publicly released. Participants can further subdivide this dataset locally into training and validation. The remaining <u>60</u> labeled cases building the <u>preliminary and final testing set</u> is only accessible for evaluation via submission to the challenge.
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