详细信息
- 来源站点
- ArXiv CS.CV
- 作者
- Xiaoqi Guo, Birui Chen, Xinquan Yang, Chaoyun Zhang, Xuefen Liu, Mianjie Zheng, Kun Tang, Xuguang Li, Wen Ma, Yanhua Xu, Linlin Shen
- 文章类型
- NEWS
- 语言
- en
- 发布日期
- 2026-06-16
摘要
arXiv:2606.16749v1 Announce Type: new Abstract: The Zygomaticomaxillary Suture is a key circummaxillary structure that connects the zygomatic bone and the maxilla, which serves as a primary site of resistance during maxillary advancement, and its maturation status directly influences the timing and efficacy of orthopedic interventions. However, accurate staging of ZMS maturation remains challenging due to subtle high-frequency transitions in suture lines and the global semantic ambiguity between adjacent stages. To address this, we present the first public ZMS dataset, comprising 3,790 ZMS images covering the entire age range from 4 to 24 years. Based on this dataset, we propose SKMamba, a Structure-aware and Knowledge-guided Mamba-based multi-modal framework for automated ZMS maturation assessment. SKMamba adopts a decoupled dual-path architecture that mimics the hierarchical diagnostic process used by experienced orthodontists.