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

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Hongwei Li , Gian Marco Conte , Syed Muhammad Anwar , Florian Kofler , Ivan Ezhov , Koen Van Leemput , Marie Piraud , María Díaz , Byrone Cole , Evan Calabrese , Jeff Rudie , Felix Meissen , Maruf Adewole , Anastasia Janas , Anahita Fathi Kazerooni , Dominic LaBella , Ahmed W. Moawad , Keyvan Farahani , J. Mark Eddy , Timothy Bergquist , Verena Chung , Russell Takeshi Shinohara , Farouk Dako , Walter F. Wiggins , Zachary J. 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 S. Kirschke , Rivka R. Colen , Aikaterini Kotrotsou , Pamela LaMontagne , Daniel Marcus , Mikhail Milchenko , Arash Nazeri , Marc‐André Weber , Abhishek Mahajan , Suyash Mohan , John Mongan , Christopher P. Hess , Soonmee Cha , Javier Villanueva‐Meyer , Errol Colak , Priscila Crivellaro , András Jakab , Jake Albrecht , Udunna Anazodo , Mariam Aboian , Thomas Yu , Verena Chung , Timothy Bergquist , J. Mark Eddy , Jake Albrecht , Ujjwal Baid , Spyridon Bakas , Marius George Linguraru , Bjoern Menze , Juan Eugenio Iglesias , Benedikt Wiestler ·

YOU? · · 2024 · Open Access ·

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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Segmentation Computer science Modalities Fluid-attenuated inversion recovery Artificial intelligence Benchmark (surveying) Image synthesis Magnetic resonance imaging Image segmentation Brain tumor Medical imaging Ground truth Computer vision Pattern recognition (psychology) Image (mathematics) Medicine Radiology Pathology Social science Geodesy Geography Sociology

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Type: preprint
Language: en
Landing Page: https://pubmed.ncbi.nlm.nih.gov/37608932
OA Status: green
Cited By: 9
References: 20
Related Works: 10
OpenAlex ID: https://openalex.org/W4386083883

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

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Type: preprint

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Language: en

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Publication year: 2024

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Publication date: 2024-11-24

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Authors: Hongwei Li, Gian Marco Conte, Syed Muhammad Anwar, Florian Kofler, Ivan Ezhov, Koen Van Leemput, Marie Piraud, María Díaz, Byrone Cole, Evan Calabrese, Jeff Rudie, Felix Meissen, Maruf Adewole, Anastasia Janas, Anahita Fathi Kazerooni, Dominic LaBella, Ahmed W. Moawad, Keyvan Farahani, J. Mark Eddy, Timothy Bergquist, Verena Chung, Russell Takeshi Shinohara, Farouk Dako, Walter F. Wiggins, Zachary J. 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 S. Kirschke, Rivka R. Colen, Aikaterini Kotrotsou, Pamela LaMontagne, Daniel Marcus, Mikhail Milchenko, Arash Nazeri, Marc‐André Weber, Abhishek Mahajan, Suyash Mohan, John Mongan, Christopher P. Hess, Soonmee Cha, Javier Villanueva‐Meyer, Errol Colak, Priscila Crivellaro, András Jakab, Jake Albrecht, Udunna Anazodo, Mariam Aboian, Thomas Yu, Verena Chung, Timothy Bergquist, J. Mark Eddy, Jake Albrecht, Ujjwal Baid, Spyridon Bakas, Marius George Linguraru, Bjoern Menze, Juan Eugenio Iglesias, Benedikt Wiestler

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Landing page: https://pubmed.ncbi.nlm.nih.gov/37608932

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OA URL: https://pmc.ncbi.nlm.nih.gov/articles/PMC10441440/pdf/nihpp-2305.09011v6.pdf

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Concepts: Segmentation, Computer science, Modalities, Fluid-attenuated inversion recovery, Artificial intelligence, Benchmark (surveying), Image synthesis, Magnetic resonance imaging, Image segmentation, Brain tumor, Medical imaging, Ground truth, Computer vision, Pattern recognition (psychology), Image (mathematics), Medicine, Radiology, Pathology, Social science, Geodesy, Geography, Sociology

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Cited by: 9

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Citations by year (recent): 2025: 3, 2024: 5, 2023: 1

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abstract_inverted_index.well-established	7
abstract_inverted_index.Computer-Assisted	110
cited_by_percentile_year.max	98
cited_by_percentile_year.min	89
countries_distinct_count	6
institutions_distinct_count	68
citation_normalized_percentile.value	0.89359905
citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	True