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  - medical
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- # Announcements
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- The paper for this dataset has been submitted for single-blind review. During the review period, access requests are temporarily disabled.
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- If you are not a reviewer, please note that downloading the dataset implies agreement with the following terms:
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- * I agree to use this dataset for non-commercial use ONLY
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- * I agree to register the GDP-HMM challenge if I use the data before the end of the challenge
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- * I understand that my access to the data may be declined/removed if I have not correctly finished above steps
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- * I agree to read the README file and follow citation terms before downloading data
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  ## Model Description
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  <!-- Provide a longer summary of what this model is. -->
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  This is a trained model can be directly used in GDP-HMM challenge in AAPM 2025.
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  Please run this model and submit to the challenge platform, please follow the instructions in https://github.com/RiqiangGao/GDP-HMM_AAPMChallenge.
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  *Attention*: This is a educational baseline that participants can quickly start the challenge and see some reasonable results. Participants may need to modify the settings and parameters to get better results.
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- - **Developed by:** Riqiang Gao
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  - **Model type:** 3D CNN, U-Shaped, MedNeXt, PyTorch-Lightning
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  - **Language(s) (NLP):** English
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  - **License:** cc-by-nc-sa-4.0
 
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+ ## Annoucements
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+ 06/2025 Updates: the top six solutions (code/weights/descriptions) of GDP-HMM challenge have been hosted here!
 
 
 
 
 
 
 
 
 
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  ## Model Description
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  <!-- Provide a longer summary of what this model is. -->
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  This is a trained model can be directly used in GDP-HMM challenge in AAPM 2025.
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  Please run this model and submit to the challenge platform, please follow the instructions in https://github.com/RiqiangGao/GDP-HMM_AAPMChallenge.
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  *Attention*: This is a educational baseline that participants can quickly start the challenge and see some reasonable results. Participants may need to modify the settings and parameters to get better results.
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+ - **Developed by:** GDP-HMM Challenge organizers and participants
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  - **Model type:** 3D CNN, U-Shaped, MedNeXt, PyTorch-Lightning
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  - **Language(s) (NLP):** English
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  - **License:** cc-by-nc-sa-4.0