The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn)

15 May 2023 · Hongwei Bran Li, Gian Marco Conte, Syed Muhammad Anwar, Florian Kofler, Ivan Ezhov, Koen van Leemput, Marie Piraud, Maria Diaz, Byrone Cole, Evan Calabrese, Jeff Rudie, Felix Meissen, Maruf Adewole, Anastasia Janas, Anahita Fathi Kazerooni, Dominic LaBella, Ahmed W. Moawad, Keyvan Farahani, Russell Takeshi Shinohara, Farouk Dako, Walter Wiggins, Zachary Reitman, Chunhao Wang, Xinyang Liu, Zhifan Jiang, Ariana Familiar, Elaine Johanson, Zeke Meier, Christos Davatzikos, John Freymann, Justin Kirby, Michel Bilello, Hassan M. Fathallah-Shaykh, Roland Wiest, Jan Kirschke, Rivka R. Colen, Aikaterini Kotrotsou, Pamela Lamontagne, Daniel Marcus, Mikhail Milchenko, Arash Nazeri, Marc André Weber, Abhishek Mahajan, Suyash Mohan, John Mongan, Christopher Hess, Soonmee Cha, Javier Villanueva, Meyer Errol Colak, Priscila Crivellaro, Andras Jakab, Udunna Anazodo, Mariam Aboian, Thomas Yu, Verena Chung, Timothy Bergquist, James Eddy, Jake Albrecht, Ujjwal Baid, Spyridon Bakas, Marius George Linguraru, Bjoern Menze, Juan Eugenio Iglesias, Benedikt Wiestler ·

Automated brain tumor segmentation methods have become well-established and reached performance levels offering clear clinical utility. These methods typically rely on four input magnetic resonance imaging (MRI) modalities: T1-weighted images with and without contrast enhancement, T2-weighted images, and FLAIR images. However, some sequences are often missing in clinical practice due to time constraints or image artifacts, such as patient motion. Consequently, the ability to substitute missing modalities and gain segmentation performance is highly desirable and necessary for the broader adoption of these algorithms in the clinical routine. In this work, we present the establishment of the Brain MR Image Synthesis Benchmark (BraSyn) in conjunction with the Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2023. The primary objective of this challenge is to evaluate image synthesis methods that can realistically generate missing MRI modalities when multiple available images are provided. The ultimate aim is to facilitate automated brain tumor segmentation pipelines. The image dataset used in the benchmark is diverse and multi-modal, created through collaboration with various hospitals and research institutions.

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