脑肿瘤分割(BraTS)挑战赛2023：用于肿瘤分割的脑MR图像合成(BraSyn)
图像与视频处理
2024-11-26 v6 计算机视觉与模式识别
摘要
自动脑肿瘤分割方法已趋于成熟，并达到了具有明确临床实用性的性能水平。这些方法通常依赖四种输入的磁共振成像(MRI)模态：含与不含对比增强的T1加权图像、T2加权图像以及FLAIR图像。然而，由于时间限制或图像伪影(如患者运动)，临床实践中常缺失部分序列。因此，替代缺失模态并提升分割性能的能力对于这些算法在临床常规中的更广泛应用是极为可取且必要的。在本工作中，我们介绍了与2023年医学图像计算与计算机辅助干预(MICCAI)会议联合建立的脑MR图像合成基准(BraSyn)。该挑战赛的主要目标是评估在提供多种可用图像时能够真实生成缺失MRI模态的图像合成方法。最终目的是促进自动化脑肿瘤分割流程。基准中使用的图像数据集具有多样性与多模态性，由多家医院及研究机构协作创建。
引用
@article{arxiv.2305.09011,
title = {The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn)},
author = {Hongwei Bran Li and Gian Marco Conte and Qingqiao Hu and Syed Muhammad Anwar and Florian Kofler and Ivan Ezhov and Koen van Leemput and Marie Piraud and Maria Diaz and Byrone Cole and Evan Calabrese and Jeff Rudie and Felix Meissen and Maruf Adewole and Anastasia Janas and Anahita Fathi Kazerooni and Dominic LaBella and Ahmed W. Moawad and Keyvan Farahani and James Eddy and Timothy Bergquist and Verena Chung and Russell Takeshi Shinohara and Farouk Dako and Walter Wiggins and Zachary Reitman and Chunhao Wang and Xinyang Liu and Zhifan Jiang and Ariana Familiar and Elaine Johanson and Zeke Meier and Christos Davatzikos and John Freymann and Justin Kirby and Michel Bilello and Hassan M. Fathallah-Shaykh and Roland Wiest and Jan Kirschke and Rivka R. Colen and Aikaterini Kotrotsou and Pamela Lamontagne and Daniel Marcus and Mikhail Milchenko and Arash Nazeri and Marc André Weber and Abhishek Mahajan and Suyash Mohan and John Mongan and Christopher Hess and Soonmee Cha and Javier Villanueva and Meyer Errol Colak and Priscila Crivellaro and Andras Jakab and Jake Albrecht and Udunna Anazodo and Mariam Aboian and Thomas Yu and Verena Chung and Timothy Bergquist and James Eddy and Jake Albrecht and Ujjwal Baid and Spyridon Bakas and Marius George Linguraru and Bjoern Menze and Juan Eugenio Iglesias and Benedikt Wiestler},
journal= {arXiv preprint arXiv:2305.09011},
year = {2024}
}
备注
Technical report of BraSyn