TRACE: Temporally Reliable Anatomically-Conditioned 3D CT Generation with Enhanced Efficiency
TRACE: 基于时间可靠性的解剖条件3D CT生成与增强效率
机构 * Department of Computer Science, Durham University(杜伦大学计算机科学系) ; Department of Automation, Tsinghua University(清华大学自动化系) ; College of Computer Science and Engineering, Dalian Minzu University(大连民族大学计算机科学与工程学院) ; Department of Engineering Science, University of Oxford(牛津大学工程科学系) ; Jarvis Research Center, Tencent YouTu Lab(腾讯YouTu实验室 Jarvis 研究中心) ; School of Engineering Mathematics and Technology, University of Bristol(布里斯托大学工程数学与技术学院) ; Medical Artificial Intelligence Laboratory, School of Engineering, Westlake University(西湖大学工程学院医学人工智能实验室)
专题命中 医学影像 :CT(title);medical image(abstract);radiology(abstract);分类 cs.CV
AI总结 TRACE通过2D多模态条件扩散方法生成具有时空对齐的3D CT图像,提升生成效率和解剖保真度。
Comments Accepted to MICCAI 2025 (this version is not peer-reviewed; it is the extended version)