--- license: cc-by-sa-4.0 --- # πŸ† Medical Segmentation Decathlon Dataset ## πŸ“ Overview The **Medical Segmentation Decathlon (MSD)** is a comprehensive benchmark dataset for validating algorithms in 3D medical image segmentation. It includes 10 distinct tasks, each with unique challenges like small data sizes, unbalanced labels, varying object scales, multi-class labels, and multimodal imaging. ## πŸ”— Dataset Access - 🌐 **Website:** [Medical Decathlon](http://medicaldecathlon.com/) - πŸ“‚ **Google Drive:** [MSD Google Drive](https://drive.google.com/drive/folders/1HqEgzS8BV2c7xYNrZdEAnrHk7osJJ--2) ## 🧩 Task Descriptions and Download Links ### 🧠 Task 01: Brain Tumours - **Target:** Gliomas segmentation (necrotic/active tumour and oedema) - **Modality:** Multimodal MRI (FLAIR, T1w, T1gd, T2w) - **Size:** 750 4D volumes (484 Training + 266 Testing) - **Source:** BRATS 2016 & 2017 datasets - **Challenge:** Complex, heterogeneously-located targets - πŸ“₯ **Download:** [Task01_BrainTumour.tar](https://msd-for-monai.s3-us-west-2.amazonaws.com/Task01_BrainTumour.tar) ### ❀️ Task 02: Heart - **Target:** Left Atrium - **Modality:** Mono-modal MRI - **Size:** 30 3D volumes (20 Training + 10 Testing) - **Source:** King’s College London - **Challenge:** Small dataset with high variability - πŸ“₯ **Download:** [Task02_Heart.tar](https://msd-for-monai.s3-us-west-2.amazonaws.com/Task02_Heart.tar) ### 🫁 Task 03: Liver - **Target:** Liver and tumour - **Modality:** Portal venous phase CT - **Size:** 201 3D volumes (131 Training + 70 Testing) - **Source:** IRCAD HΓ΄pitaux Universitaires - **Challenge:** Unbalanced labels with large (liver) and small (tumour) targets - πŸ“₯ **Download:** [Task03_Liver.tar](https://msd-for-monai.s3-us-west-2.amazonaws.com/Task03_Liver.tar) ### 🧬 Task 04: Hippocampus - **Target:** Hippocampus head and body - **Modality:** Mono-modal MRI - **Size:** 394 3D volumes (263 Training + 131 Testing) - **Source:** Vanderbilt University Medical Center - **Challenge:** High-precision segmentation of small neighboring structures - πŸ“₯ **Download:** [Task04_Hippocampus.tar](https://msd-for-monai.s3-us-west-2.amazonaws.com/Task04_Hippocampus.tar) ### πŸ§‘β€βš•οΈ Task 05: Prostate - **Target:** Prostate central gland and peripheral zone - **Modality:** Multimodal MRI (T2, ADC) - **Size:** 48 4D volumes (32 Training + 16 Testing) - **Source:** Radboud University Medical Centre - **Challenge:** Segmenting two adjacent regions with large variations - πŸ“₯ **Download:** [Task05_Prostate.tar](https://msd-for-monai.s3-us-west-2.amazonaws.com/Task05_Prostate.tar) ### 🌬️ Task 06: Lung - **Target:** Lung and tumours - **Modality:** CT - **Size:** 96 3D volumes (64 Training + 32 Testing) - **Source:** The Cancer Imaging Archive - **Challenge:** Small target (cancer) in a large image - πŸ“₯ **Download:** [Task06_Lung.tar](https://msd-for-monai.s3-us-west-2.amazonaws.com/Task06_Lung.tar) ### πŸƒ Task 07: Pancreas - **Target:** Pancreas and tumour - **Modality:** Portal venous phase CT - **Size:** 420 3D volumes (282 Training + 139 Testing) - **Source:** Memorial Sloan Kettering Cancer Center - **Challenge:** Unbalanced labels with large, medium, and small structures - πŸ“₯ **Download:** [Task07_Pancreas.tar](https://msd-for-monai.s3-us-west-2.amazonaws.com/Task07_Pancreas.tar) ### 🩸 Task 08: Hepatic Vessels - **Target:** Hepatic vessels and tumour - **Modality:** CT - **Size:** 443 3D volumes (303 Training + 140 Testing) - **Source:** Memorial Sloan Kettering Cancer Center - **Challenge:** Small, tubular structures near a heterogeneous tumour - πŸ“₯ **Download:** [Task08_HepaticVessel.tar](https://msd-for-monai.s3-us-west-2.amazonaws.com/Task08_HepaticVessel.tar) ### 🌿 Task 09: Spleen - **Target:** Spleen - **Modality:** CT - **Size:** 61 3D volumes (41 Training + 20 Testing) - **Source:** Memorial Sloan Kettering Cancer Center - **Challenge:** Large foreground size variation - πŸ“₯ **Download:** [Task09_Spleen.tar](https://msd-for-monai.s3-us-west-2.amazonaws.com/Task09_Spleen.tar) ### 🩹 Task 10: Colon - **Target:** Colon Cancer Primaries - **Modality:** CT - **Size:** 190 3D volumes (126 Training + 64 Testing) - **Source:** Memorial Sloan Kettering Cancer Center - **Challenge:** Heterogeneous appearance - πŸ“₯ **Download:** [Task10_Colon.tar](https://msd-for-monai.s3-us-west-2.amazonaws.com/Task10_Colon.tar) ## πŸ“œ License The data is available under a permissive CC-BY-SA 4.0 license, allowing sharing, distribution, and further development. ## πŸ–‹οΈ Citation Please cite the following paper when using this dataset: **[A large annotated medical image dataset for the development and evaluation of segmentation algorithms](https://arxiv.org/abs/1902.09063)** ## πŸ“ Assessment Metrics Performance is evaluated using: - πŸ₯‡ **Dice Score (DSC)** - πŸ“ **Normalized Surface Distance (NSD)** ## πŸ“¬ Contact For questions, please reach out to the organizers at: medicaldecathlon@gmail.com