Challenge Tasks
The SegRap2025 Challenge focuses on accurate Gross Tumor Volume (GTV) and Lymph Node Clinical Target Volume (LN CTV) segmentation in Computed Tomography (CT) images, aiming to support clinical manual delineation, enhance research on radiation dose calculation, and improve efficiency of radiotherapy treatment planning.
Task01: GTV Segmentation
Accurately delineate Gross Target Volume of nasopharynx (GTVnx, also named GTVp) and Gross Target Volume of lymph node (GTVnd) within paired non-contrast computed tomography (ncCT) and contrast computed tomography (ceCT) images.
SegRap2025 Dataset will consist of CT images collected by Siemens CT scanners with the following scanning conditions: bulb voltage, 120 kV; current, 300 mA; scan thickness, 3.0 mm; resolution, 1024 × 1024 or 512 × 512; injected contrast agent, iohexol (volume, 60~80 mL; rate, 2 mL/s; without delay). The dataset consists of clinically required non-contrast CT images (ncCT) and contrast CT images (ceCT) from patients with nasopharyngeal cancer before treatment.
The dataset consists of clinically required non-contrast CT images (ncCT) and contrast CT images (ceCT) from patients with nasopharyngeal cancer before treatment.
- Training data will consist of CT images from 120 patients with a corresponding label map, as well as 500 unlabeled cases.
- Validation data will consist of CT images from 20 patients.
- Testing data will consist of CT images from 60 patients from internal testing cohort and 60 patients from external testing cohort.
Note: All GTVs were annotated individually by oncologists using MIM Software and ITKSNAP, the annotation of each organ was also stored individually. The expected output from your algorithm should be a set of label maps.
Coming soon!
Task02: LN CTV Segmentation
Accurately delineate 6 LN CTVs: L_Ib, L_II+III+Va, L_IV+Vb+Vc, R_Ib, R_II+III+Va, and R_IV+Vb+Vc within paired ncCT and ceCT images or ncCT/ceCT images.
SegRap2025 Dataset will consists of CT images from Sichuan Cancer Hospital are collected by a Brilliance CT Big Bore system from Philips Healthcare (Philips Healthcare, Best, the Netherlands), with the following scanning conditions: bulb voltage at 120 kV, current ranging from 275 to 375 mA, slice thickness of 3.0 mm, and full resolution of 512 × 512. An injected contrast agent, iohexol, was used during the ceCT examination. Similarly, CT images from Sichuan Provincial People's Hospital, The First Affiliated Hospital of University of Science and Technology of China and Southern Medical University were acquired using a Somatom Definition AS 40 system from Siemens Healthcare (Siemens Healthcare, Forcheim, Germany), with the following conditions: bulb voltage ranging from 120 to140 kV, current ranging from 280 to 380 mA, slice thickness of 3.0 mm, and full resolution of 512 × 512. CT images from Daguan Hospital of Chengdu Jinjiang were acquired using a Somatom Definition AS 40 system from Siemens Healthcare (Siemens Healthcare, Forcheim, Germany), with the following conditions: bulb voltage 120 kV, current ranging from 200 to 250 mA, slice thickness of 2.5 mm, and full resolution of 512 × 512.
The dataset consists of clinically required non-contrast CT images (ncCT) and/or contrast CT images (ceCT) from patients with nasopharyngeal cancer before treatment.
- Training data will consist of CT images from 262 patients from five cohorts (150 paired CT, 32 ncCT and 90 ceCT) with a corresponding label map, as well as 500 unlabeled cases.
- Validation data will consist of CT images from 40 patients from external testing cohort (20 paired CT, 10 ncCT and 10 ceCT).
- Testing data will consist of CT images from 100 patients from external testing cohort (40 paired CT, 30 ncCT and 30 ceCT).
Note: All LN CTVs were annotated individually by oncologists using MIM Software and ITKSNAP, the annotation of each organ was also stored individually. The expected output from your algorithm should be a set of label maps.
Coming soon!