Brain Tumor AI Challenge (2021)

This competition, organized in partnership with the American Society of Neuroradiology (ASNR) and the Medical Image Computing and Computer Assisted Interventions (MICCAI) Society, focused on brain tumor detection and classification, utilizing multi-parametric magnetic resonance imaging (mpMRI) scans. It was the culmination of a decade of Brain Tumor Segmentation (BraTS) challenges and created a large and diverse dataset including detailed annotations and an important associated biomarker.

Overview

The Brain Tumor AI Challenge comprised two tasks related to brain tumor detection and classification. Participants could choose to compete in one or both. Both challenge tasks launched in July 2021, with final submissions due in October and validated results announced in November. A challenge recognition event was held at the RSNA annual meeting on November 29, 2021.

Dataset

Review the Brain Tumor AI Challenge dataset description.

Sponsors

Prize money for the top entries in each task was provided by Intel, NeoSoma and RSNA.

Intel                 Neosoma    

Prizes awarded for each task were:

  • 1st: $6,000
  • 2nd: $5,000
  • 3rd: $4,000
  • 4th-8th: $3,000 each

Task 1: Brain Tumor Segmentation

Participants built models to produce detailed segmentations of brain tumor sub-regions. Such segmentations could enable improvements in computer-assisted surgery, radiotherapy guidance and disease progression monitoring.

Winning teams and entries

Top entries in the Segmentation Task were submitted by:

Team name Members Video
KAIST-MRI-Lab Huan Minh Luu
Sung-Hong Park
Video
deepX Yading Yuan Video
mfnv Michal Futrega
Alexandre Milesi
Michal Marcinkiewicz
Pablo Ribalta Lorenzo
 
NVAUTO Andriy Myronenko
Mahfuzur Rahman
Siddiquee
 
FightBrainTumor Jun Ma
Jianan Chen
Future-Processing-Healthcare Jakub Nalepa
Krzysztof Kotowski
Szymon Adamski
Bartosz Machura
Lukasz Zarudzki
NGresearch Jianxun Ren
NPU_PITT Yong Xia
Haozhe Jia
Chao Ba
Weidong Cai
Heng Huang
Team name: KAIST-MRI-Lab
Members: Huan Minh Luu
Sung-Hong Park
Video: Video
Team name: deepX
Members: Yading Yuan
Video: Video
Team name: mfnv
Members: Michal Futrega
Alexandre Milesi
Michal Marcinkiewicz
Pablo Ribalta Lorenzo
Video:  
Team name: NVAUTO
Members: Andriy Myronenko
Mahfuzur Rahman
Siddiquee
Video:  
Team name: FightBrainTumor
Members: Jun Ma
Jianan Chen
Video:
Team name: Future-Processing-Healthcare
Members: Jakub Nalepa
Krzysztof Kotowski
Szymon Adamski
Bartosz Machura
Lukasz Zarudzki
Video:
Team name: NGresearch
Members: Jianxun Ren
Video:
Team name: NPU_PITT
Members: Yong Xia
Haozhe Jia
Chao Ba
Weidong Cai
Heng Huang

Video:

Task 2: Brain Tumor Radiogenomic Classification

Participants built models that use mpMRI imaging to predict MGMT promoter methylation status, an important biomarker for treatment of brain tumors. Such radiogenomic models could improve the efficiency and accuracy of diagnosis, prognosis and treatment planning for patients with glioblastoma.

Winning teams and entries

The top entries in the radiogenomic classification task were submitted by:

Team name Members Solution Video
Tunisia.ai Firas Baba Solution
Minh Phan Minh Phan Solution Video
Cedric Soares Cedric Soares Solution
Leaky Folds David Roberts
Assam Guahati
Solution
random Bhavesh Tangirala Solution
Train4Ever Tung Vu Son
Truong Bui Nhat
Nam Nguyen The
Tuyen Dam Trong
Khanah Vu Day
Solution
Igor Lashkov Igor Lashkov Solution
ArturHugo Artur HC Pereira Solution
Team name: Tunisia.ai
Members: Firas Baba
Solution: Solution
Video:
Team name: Minh Phan
Members: Minh Phan
Solution: Solution
Video: Video
Team name: Cedric Soares
Members: Cedric Soares
Solution: Solution
Video:
Team name: Leaky Folds
Members: David Roberts
Assam Guahati
Solution: Solution
Video:
Team name: random
Members: Bhavesh Tangirala
Solution: Solution
Video:
Team name: Train4Ever
Members: Tung Vu Son
Truong Bui Nhat
Nam Nguyen The
Tuyen Dam Trong
Khanah Vu Day
Solution: Solution
Video:
Team name: Igor Lashkov
Members: Igor Lashkov
Solution: Solution
Video:
Team name: ArturHugo
Members: Artur HC Pereira
Solution: Solution
Video: