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The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma.

Authors :
LaBella D
Adewole M
Alonso-Basanta M
Altes T
Anwar SM
Baid U
Bergquist T
Bhalerao R
Chen S
Chung V
Conte GM
Dako F
Eddy J
Ezhov I
Godfrey D
Hilal F
Familiar A
Farahani K
Iglesias JE
Jiang Z
Johanson E
Kazerooni AF
Kent C
Kirkpatrick J
Kofler F
Leemput KV
Li HB
Liu X
Mahtabfar A
McBurney-Lin S
McLean R
Meier Z
Moawad AW
Mongan J
Nedelec P
Pajot M
Piraud M
Rashid A
Reitman Z
Shinohara RT
Velichko Y
Wang C
Warman P
Wiggins W
Aboian M
Albrecht J
Anazodo U
Bakas S
Flanders A
Janas A
Khanna G
Linguraru MG
Menze B
Nada A
Rauschecker AM
Rudie J
Tahon NH
Villanueva-Meyer J
Wiestler B
Calabrese E
Source :
ArXiv [ArXiv] 2023 May 12. Date of Electronic Publication: 2023 May 12.
Publication Year :
2023

Abstract

Meningiomas are the most common primary intracranial tumor in adults and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on multiparametric MRI (mpMRI) for diagnosis, treatment planning, and longitudinal treatment monitoring; yet automated, objective, and quantitative tools for non-invasive assessment of meningiomas on mpMRI are lacking. The BraTS meningioma 2023 challenge will provide a community standard and benchmark for state-of-the-art automated intracranial meningioma segmentation models based on the largest expert annotated multilabel meningioma mpMRI dataset to date. Challenge competitors will develop automated segmentation models to predict three distinct meningioma sub-regions on MRI including enhancing tumor, non-enhancing tumor core, and surrounding nonenhancing T2/FLAIR hyperintensity. Models will be evaluated on separate validation and held-out test datasets using standardized metrics utilized across the BraTS 2023 series of challenges including the Dice similarity coefficient and Hausdorff distance. The models developed during the course of this challenge will aid in incorporation of automated meningioma MRI segmentation into clinical practice, which will ultimately improve care of patients with meningioma.

Details

Language :
English
ISSN :
2331-8422
Database :
MEDLINE
Journal :
ArXiv
Accession number :
37608937