Harnessing Lightweight Transformer with Contextual Synergic Enhancement for Efficient 3D Medical Image Segmentation
利用轻量级Transformer与上下文协同增强进行高效的3D医学图像分割
机构 * Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR(电子工程系,香港中文大学(深圳)Hong Kong SAR) ; Centre for Artificial Intelligence and Robotics (CAIR), Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong SAR(人工智能与机器人中心(CAIR),香港科学与创新研究院,中国科学院,Hong Kong SAR)
AI总结 本文提出Light-UNETR,通过轻量级维度缩减注意力模块和紧凑门控线性单元提升模型效率,结合上下文协同增强策略提高数据效率,在少量标注数据下实现高效3D医学图像分割。
Comments Accepted to IEEE TPAMI