A spinal orthopedic surgery segment intelligent prediction method based on fusion of standing position orthogonal X-ray and lying position CT data of a spine
By integrating orthogonal X-ray data of the spine in standing position and CT data in supine position, and combining them with clinical indicators, a method for predicting spinal surgical segments was constructed. This method solves the problems of insufficient utilization of complementary information from image modalities and inadequate integration of clinical information in existing technologies, and achieves precise spinal surgical planning and segment-level operability.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NANJING UNIV
- Filing Date
- 2026-02-09
- Publication Date
- 2026-05-29
AI Technical Summary
Existing technologies struggle to fully utilize the complementary information between orthogonal X-ray and CT data, and the integration of clinical information and imaging features is insufficient, resulting in inadequate accuracy and operability in spinal surgery decisions, particularly at the segmental level where clear modeling is lacking.
By integrating orthogonal X-ray data of the spine in standing position and CT data in supine position, and combining it with the patient's clinical indicators, a complete technical process is constructed from key point detection, three-dimensional segmentation to surgical segment prediction, including key point localization, spinal repositioning and segmental analysis, to achieve unified normalization of multimodal data, rigid body repositioning and regulation of clinical conditions.
It enables a comprehensive and precise depiction of the spinal morphology, improves the accuracy and operability of surgical decisions, reduces the workload of doctors, and provides stable and objective support for spinal surgery planning.
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