arXiv · cs.AI · Yuting He, Xu Wen, Hongxing Lan, Chengliang Liu, Yuxing Liu, Yan Xi, Wenxue Yu, Jindi Kong, Zhiqiang Zhang, Liang Jiang, Rongjun Ge, Yang Chen, Multi-Center Cooperative Clinical Study Group for "Lesion-Phenotype Brain Mapping in Acute Stroke" · 9 小时前模型评分58
BrainGFM：面向计算脑影像的生成式基础模型
A generative foundation model for computational brain imaging
导读
研究团队提出生成式基础模型 BrainGFM，用约 130 万张 MRI 和 CT 切片预训练，把知识迁移从复用表征扩展到可复用、可重构的脑影像先验。该模型在 48 个下游任务上改善了有限监督下的分割与分类，并在 4,796 名卒中患者的多中心临床验证中覆盖三项临床相关任务。
分类置信度
中 · 待人工复核
- 只有单一媒体来源，需要人工复核。
来源级别：媒体与个人
应用领域：医疗与生命科学
事件类型：研究发布
证据摘录
- “This paper proposes BrainGFM, a generative foundation model that extends knowledge transfer beyond representation reuse through a reusable and reconfigurable brain-imaging prior.”
- “By pretraining on a corpus of about 1.3 million MRI and CT slices, BrainGFM supported task-aligned data synthesis for low-data predictive learning and task-adapted post-training for image reconstruction.”
- “Multicenter clinical validation involving 4,796 stroke patients across two internal and four external centers demonstrated its applicability to three clinically relevant tasks around stroke cohorts.”
来源：arXiv · cs.AI · arxiv.org