ECCV 2022 Workshop: AI-enabled Medical Image Analysis – Digital Pathology & Radiology/COVID19

                         2nd COV19D Competition

The Workshop “AI-enabled Medical Image Analysis – Digital Pathology & Radiology/COVID19” will be held in conjunction with European Conference on Computer Vision (ECCV) 2022 in Tel-Aviv, Israel, 23 – 24 October, 2022. The following information describes the submission procedure to the 2nd COV19D Competition which is a part of the Workshop.

For any requests or enquiries, please contact: stefanos@cs.ntua.gr

Organizers

• Stefanos Kollias (National Technical University Athens, Institute Computer Communication Systems)
  
• Xujiong Ye ( University of Lincoln )                                                xye@lincoln.ac.uk 
• Luc Bidaut ( University of Lincoln )                                                lbidaut@lincoln.ac.uk 
• Francesco Rundo ( STMicroelectronics ADG—Central R&D )    francesco.rundo@st.com 
• Dimitrios Kollias ( Queen Mary University London )                   d.kollias@qmul.ac.uk 
• Giuseppe Banna ( Portsmouth Hospitals Univ. NHS Trust )      giuseppe.banna@nhs.net

Data Chairs

• Anastasios Arsenos ( National Technical University of Athens )
• Paraskevi Theofilou (National Technical University of Athens )
• Manos Seferis ( National Technical University of Athens )
• James Wingate ( University of Lincoln )

Description

1. Scope

The 2nd COV19D Competition follows the 1st Competition held in the framework of the MIA-COV19D Workshop in ICCV 2021. It includes two Challenges: i) COVID19 Detection Challenge and ii) COVID19 Severity Detection Challenge.

Both Challenges are  based on an extended version of the database used in the 1st COV19D Competition, including  chest CT scan series. It consists of  1,650 COVID and 6,100 non- COVID
chest CT scan series. Each chest CT scan series consists of a sequence of 2-D CT slices, the number of which is between 50 and 700.

I. COVID19 Detection Challenge

Each CT scan is manually annotated with respect to Covid-19 and non-Covid-19 categories. The database is split into training, validation and test partitions. The training and validation sets along with their corresponding annotations will be provided to the Competition participating teams to develop AI/ML/DL models for Covid-19 and non-Covid-19 prediction. Performance of the different approaches will be evaluated on the test set in terms of the ‘macro’ F1 score.

II. COVID19 Severity Detection Challenge

Part of the database has been annotated in terms of COVID-19 severity into four categories, i.e., mild, moderate, severe and critical. The database is split into training, validation and test partitions. The training and validation sets along with their corresponding annotations will be provided to the Competition participating teams to develop AI/ML/DL models for Covid-19 severity prediction. Performance of the different approaches will be evaluated on the test set in terms of the ‘macro’ F1 score.

2. Call for Participation

The participating teams are invited to participate in at least one of these Challenges. In the end, they will submit their Covid-19 predictions and/or Covid-19 severity predictions for the respective test datasets. The winners of the Competitions will be selected based on the achieved performance, in terms of the ‘macro’ F1 score, on the test sets.

There will be one winning team for each Competition. The top-3 performing teams are expected to contribute a paper describing their approach, methodology and results to our “AI-enabled Medical Image Analysis – Digital Pathology & Radiology/COVID19” ECCV Workshop. All other teams will be able to submit a paper describing their solutions and final results to the Workshop. The accepted papers will be part of the ECCV 2022 proceedings. 

The research groups will be able to use any publicly available datasets as long as they report it in their submitted final paper. We will provide a white paper describing the Competitions, the databases used, as well as baseline models and their results for comparison purposes.

3. General Information

In order to participate in the Competitions, teams will need to register. At the end of the Competitions, each team will have to send us: i) their predictions on the test set, ii) a link to a Github repository where their solution/source code will be stored, and iii) a link to an ArXiv paper with 2-8 pages describing their proposed methodology, data used and results. After that, the winner of each Competition will be announced and a leaderboard will be published. The winner and the two runner-ups in each Competition will be asked to also share their trained models so as to check out the validity of the approach.

4. Participation Information

In order to participate, teams will have to register; the lead researcher should send an email from their official address (no personal emails will be accepted) to d.kollias@qmul.ac.uk with:

i) subject “2nd COV19D Competition: Team Registration”;
ii)  this EULA filled in, signed and attached;
iii) the lead researcher’s official academic/industrial website; please note that the lead researcher cannot be a student (UG/PG/Ph.D.);
iv) the emails of each team member
v) the team’s name
vi) the point of contact name and email address (which member of the team will be the main point of contact for future communications, data access etc)

There is a maximum number of 8 participants in each team.

As a reply, you will receive access to the dataset’s images and annotations.

5. Final Paper Submission Information

The peer review process for the papers will be double blind, including at least two distinct reviews per submission, and will follow ECCV standards and policies. The accepted papers will be part of ECCV 2022 conference proceedings. All paper submissions must adhere to the ECCV 2022 paper submission style, format, and length restrictions. Please have a look here.

The submission process will be handled through the CMT of the main Workshop.

6. Important Dates (UPDATED)

The timeline for the competitions will be as follows:

• May 9, 2022: Opening of the Competition; start of registration of research groups;  provision of training and validation datasets, of respective annotations and of the baseline approach will follow
• July 4, 2022: Final submission of results deadline (Results, Code and ArXiv paper sent to d.kollias@qmul.ac.uk)
• July 8, 2022: Winners announcement
• July 15, 2022: Final paper submission deadline (at AIMIA Workshop’s CMT)
• August 5, 2022: End of review period – review decisions sent to authors; notifications of acceptance
• August 12, 2022: Camera ready version deadline

7. Competition Results (NEW!)

28 Teams participated in the 2nd COV19D Competition (COVID19 Detection Challenge and COVID19 Severity Detection Challenge).

14 Teams submitted their results to the (2nd) COVID19 Detection Challenge; 9 Teams submitted their results to the (1st) COVID19 Severity Detection Challenge.

9 and 6 Teams scored higher than the baseline and made valid submissions, respectively; their results are shown in the leaderboards below.

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There are two winners of the (2nd) COVID19 Detection Challenge!

– The team ACVLab consisting of: Chih-Chung Hsu, Chi-Han Tsai, Guan-Lin Chen, Sin-Di Ma
and Shen-Chieh Tai (National Cheng Kung University, Taiwan)

– The team FDVTS_COVID consisting of: Junlin Hou, Jilan Xu, Rui Feng, and Yuejie Zhang (Fudan
University, China).

The runner-up is team MDAP consisting of: Robert Turnbull (Melbourne Data Analytics Platform, Australia).

The team that ranked third is Code 1055 consisting of:  Daniel Kienzle, Julian Lorenz, Katja Ludwig , Robin Schön  and Rainer Lienhart (Augsburg University, Germany).

The leaderboard can be found  here

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The winner of the (1st) COVID19 Severity Detection Challenge is team FDVTS_COVID consisting of: Junlin Hou, Jilan Xu, Rui Feng, and Yuejie Zhang (Fudan University, China).

The runner-up is team Code 1055 consisting of:  Daniel Kienzle, Julian Lorenz, Katja Ludwig , Robin Schön  and Rainer Lienhart (Augsburg University, Germany).

The team that ranked third is CNR-IEMN consisting of: Fares Bougourzi, Cosimo Distante (National Research Council of Italy, Italy)  Fadi Dornaika (University of the Basque Country UPV/EHU,  Spain), Abdelmalik Taleb-Ahmed (Université Polytechnique Hauts de France, France).

The leaderboard can be found here

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Congratulations to you all, winning and non-winning teams! Thank you very much for participating in our Competition.

All teams are invited to submit their methodologies-papers (please see 5 above). All accepted papers will be part of the ECCV 2022 proceedings.

We are looking forward to receiving your submissions!

References