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lld-mmri2023's Introduction

Liver Lesion Diagnosis Challenge on Multi-phase MRI (LLD-MMRI2023).


🆕 News

  • 2023-2-28: 🔥🔥🔥Dataset Release.

    • The dataset is accessible at here. We provide annotations for an additional 104 cases (i.e., test set), which is not incorporated within this challenge.
  • 2023-9-8: Final Leaderboard for Test Release.

    • You can address the leaderboard here, where you can also address the codes of the top-5 teams.
  • 2023-8-8: Leaderboard for Test Release.

    • The leaderboard is presented. Please note that this is only a temporary ranking. We ask the top five teams to publish their code within two weeks. Failure to submit your code by the designated deadline will result in removal from the leaderboard and the ranking will be postponed.
  • 2023-7-10: Validation Stage Completed.

    • The leaderboard is presented according to the highest metrics over the three submissions.
  • 2023-7-7: Last Result Submission on Validation Set.

    • The submission window is open from 00:00 to 24:00 on Jul 7th. Only the last submission within this timeframe will be considered. Early or late submissions will not be processed.
  • 2023-6-19: Leaderboard for the Second Submission on Validation Set Release.

    • You can address the leaderboard here.
  • 2023-6-18: Registration Close.

    • The registration channel is now closed.
    • We will release the download link of the dataset after the challenge is completed.
  • 2023-6-16: Second Result Submission on Validation Set.

    • The submission window is open from 00:00 to 24:00 on Jun 16th. Only the last submission within this timeframe will be considered. Early or late submissions will not be processed.

    • The corresponding person should send the JSON file, which should be named using your team name (e.g., TeamName.json), and the subject line of the email should follow this format: Prediction submission-Your Registered Team Name (e.g., Prediction submission-TeamName).

    • Specific precautions have been sent to the corresponding person by email, if you do not receive the email, please contact us at [email protected].

  • 2023-5-29: Leaderboard for the First Submission on Validation Set Release.

    • You can download the leaderboard here.
  • 2023-5-26: First Result Submission on Validation Set.

    • The submission window is open from 00:00 to 24:00 on May 26th. Only the last submission within this timeframe will be considered. Early or late submissions will not be processed.

    • The corresponding person should send the JSON file, which should be named using your team name (e.g., TeamName.json), and the subject line of the email should follow this format: Prediction submission-Your Registered Team Name (e.g., Prediction submission-TeamName).

    • Specific precautions have been sent to the corresponding person by email, if you do not receive the email, please contact us at [email protected].

  • 2023-4-28: Code and Training/Validation Dataset Release.

    • We’ve enabled access to the baseline code here and released training/validation dataset via email. Participants who successfully registered as of April 28th have received emails with data download link , if not, please contact us with your team name at [email protected].

    • Participants who registered after April 28th will receive an email with data link within three working days.

  • 2023-4-14: Registration Channel Now Open for Participants

    • Registration channel for the upcoming LLD-MMRI2023 is now open! Please complete the registration form and you will receive an email from LLD-MMRI2023 group within 3 days. We look forward to welcoming you there!
  • 2023-3-4: Our challenge proposal has been accepted by MICCAI 2023.

🎯 Objective

Liver cancer is a severe disease that poses a significant threat to global human health. To enhance the accuracy of liver lesion diagnosis, multi-phase contrast-enhanced magnetic resonance imaging (MRI) has emerged as a promising tool. In this context, we aim to initiate the inaugural Liver Lesion Diagnosis Challenge on Multi-phase MRI (LLD-MMRI2023) to encourage the development and advancement of computer-aided diagnosis (CAD) systems in this domain.

📝 Registration (Closed)

Registration is currently underway. We kindly request participants to accurately and thoroughly complete the registration form. The registration outcome will be communicated via email within 3 days. Please check for spam if you do not receive a reply for a long time.
Note: Registration channel will close on June 17th.

📁 Dataset

Note: The dataset is restricted to research use only, you can not use this data for commercial purposes.

  1. The training set, validation set, and test set will be made available in three stages. The training dataset (with annotations) and the validation dataset (without annotations) will be released first on April 28th. Annotations on the validation set will be accessible on July 8th, and the test dataset (without annotations) will be released on August 2nd.
  2. The datasets include full volume data, lesion bounding boxes, and pre-cropped lesion patches.
  3. The dataset comprises 7 different lesion types, including 4 benign types (Hepatic hemangioma, Hepatic abscess, Hepatic cysts, and Focal nodular hyperplasia) and 3 malignant types (Intrahepatic cholangiocarcinoma, Liver metastases, and Hepatocellular carcinoma). Participants are required to make a diagnosis of the type of liver lesion in each case.
  4. Each lesion has 8 different phases, providing diverse visual cues.
  5. The dataset proportion is as follows:
    Training cases: 316
    Validation cases: 78
    Test cases: 104
  • April 28th: Release the training set (with annotations), validation set (without annotations), and baseline code
  • July 8th: Release the annotations of the validation set
  • August 2nd: Release the test set (without annotations)

🖥️ Training

We shall provide the code for data loading, model training/evaluation, and prediction in this repository. Participants can design and evaluate their models following the provided baseline. The code will be published on April 28th.
Note: Additional public datasets are allowed for model training and/or pre-training, but private data is not allowed.

🖥️ Prediction

We highly suggest using our provided code to generate predictions.
Note: If participants intend to use their prediction style, please ensure that the format of the prediction results is exactly the same as the template we provide.
The code will be published on April 28th.

📤 Submission

Participants should send their prediction results to the designated email address (the email address will be notified by email to the registered participants), and we shall acknowledge receipt.
Note: The challenge comprises four evaluation stages. In the first three stages, we shall update the ranking based on the predicted results of the algorithm on the validation set. Participants will have a 24-hour submission window on May 26th, June 16th, and July 7th to submit their prediction results. On July 8th, annotations on the validation set will be released to further support model design and training. In the final stage, the test set (without annotations) will be released on August 2nd. Participants are required to submit their predictions on August 4th, and the predicted results at this stage will determine the final ranking.

  • May 26th: The first submission of the predicted results on the validation set
  • June 16th: The second submission of the predicted results on the validation set
  • July 7th: The third submission of the predicted results on the validation set
  • August 4th: The submission of the predicted results on the test set (this will be used for the final leaderboard).

🏆 Leaderboard

We shall present and update the leaderboard on our website.
The ranking shall be determined by the average of the F1-score and Cohen's Kappa coefficient.

🔍 Verification

To ensure fairness in the challenge, we do not allow to use private data. You have to ensure the reproducibility of the model. The top 10 teams will be required to disclose their codes and model weights on GitHub or other publicly accessible websites for verification. We shall use these codes and model weights to verify that the reproduced results are consistent with the submitted predictions. Failure to disclose codes and model weights within the stipulated time frame shall lead to removal from the leaderboard. In case of serious discrepancies detected using disclosed codes and model weights, we shall notify the corresponding teams to take remedial actions. Failure to comply within the allotted time will lead to removal from the leaderboard, and the leaderboard will be adjusted accordingly. New teams that subsequently enter the top 10 will also be required to comply with the same rules. If you use additional public datasets, you also need to disclose them; however, such disclosure will not impact your ranking.

🏅 Announcement

  1. All the results shall be publicly displayed on the leaderboard.
  2. The top 5 teams on the leaderboard shall be invited to give a 5-10 minute presentation for the MICCAI2023 challenge session.
  3. The prizes are as follows:
    🥇 First prize: US$3,000 for one winner;
    🥈 Second prize: US$1,000 for one winner;
    🥉 Third prize: US$500 for two to three winners.

🤝 Acknowledgement

We would like to acknowledge the following organizations for their support in making this challenge possible:
Ningbo Medical Center Lihuili Hospital for providing the dataset.
Deepwise Healthcare and The University of Hong Kong for organizing and providing funding for the challenge.

📧 Contact

Should you have any questions, please feel free to contact the organizers at [email protected] or open an issue.

lld-mmri2023's People

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lld-mmri2023's Issues

I can't decompress the concatenated dataset zip file

Like this issue "#1", I used the command "type lld_mmri2023_part0* > lld_mmri2023.zip" to concatenate the dataset files to a new dataset file. But I also can't decompress the new dataset file. Additionally, I use the command "unzip lld_mmri2023.zip", it shows a error "Trying to read large file (> 2 GiB) without large file support".
The Windows system is used to conduct these operations.

No access to validation set labels

Dear LLD-MMRI 2023 Team,

could you please provide more information about how to access the labels of the validation set?

Thanks in advance!

Data Link

Hi! My team "Liuhuhu" already filled in the registration information, but we have not received the data link, plz tell us if there is anything wrong.Thanks!

Spacing information is listed in 'Annotation.json'

Hello,
I checked the full image using ITK-SNAP and I found that the shown spacing is 1x1x1mm which is inconsistent with the true data volume. Maybe the authors only change the nii files' head but not resample the nii volume?
Screen Shot 2023-04-28 at 7 06 09 PM

The performance of baseline I run seems error

I run the baseline, but the results seem a bit incorrect.
I achieve the best value in validation:
acc: 0.36923076923076925
f1: 0.24474850546279117
recall: 0.2687074829931973
precision: 0.2650609080841639
kappa: 0.16718749999999993
The performance is too low. Can you provide the classification performance of baseline you running?

Inquiry about the Release of Validation Set Annotations

Dear Competition Organizer's,

I am writing to inquire about the release of the annotations for the validation set. As per the schedule provided, it was mentioned that the annotations would be released on July 8th. However, to date, I have not been able to access the annotations.

I would be grateful if you could kindly provide an update regarding the release of the annotations for the validation set.Having access to the validation set annotations is crucial for participants like me to evaluate and refine our models effectively.

Thank you very much for your attention to this matter. I look forward to your response and appreciate your assistance in resolving this issue.

Repetitive slices in some in and out phases.

Hello,
I apologize for bothering again.
I have noticed that some cases exhibit repetitive slices in both their "in" and "out" phases.
For example, in case MR2603, the upper part of the kidney is repeated twice.
Screen Shot 2023-06-06 at 6 21 05 PM
Screen Shot 2023-06-06 at 6 21 31 PM
Also cases like MR3573 MR13219 MR17022 MR17217 (maybe others) have the same issue.
Screen Shot 2023-06-06 at 6 26 41 PM

I am feeling somewhat confused because if I intend to incorporate a registration method into my pipeline, these repetitive slices could potentially impact its performance. Do you have any suggestions on how to address this issue? Is it necessary to repair it?

Has the data been resampled?

Hi!
I used the code 'image.GetSpacing()' and found that the voxel of all data is (1.0, 1.0, 1.0). Has the data been resampled?

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