Anatomical Segmentation With 3D–2D Registration for Spinal Navigation
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Solution Overview
Problem
Surgeries involving spinal manipulation pose a risk of neurological deficit due to the proximity of neural structures, necessitating precise intraoperative imaging to guide surgical instruments safely through or near these structures.
Innovation Solution
A method involving the use of three-dimensional image datasets for surgical site segmentation, registration with two-dimensional images, and display of segmented anatomical features to assist in navigating surgical instruments safely during procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If intraoperative imaging is used to guide surgical instruments near neural structures, then surgical precision is improved, but device complexity increases
Solution Approach 1:
The imaging system segments the surgical site into distinct anatomical structures (vertebrae, neural elements, soft tissues) using 3D image datasets. This segmentation allows precise identification and navigation relative to neural structures while managing system complexity through modular image processing
Solution Approach 2:
The system transforms 2D intraoperative images into 3D registered representations by integrating preoperative 3D image datasets with intraoperative 2D imaging. This dimensional enhancement provides comprehensive spatial awareness of neural structures without requiring complex multi-modal imaging hardware
2Measurement precision
If three-dimensional image datasets are processed for anatomical segmentation, then measurement precision is improved, but loss of time increases
Solution Approach 1:
Preoperative 3D image datasets are acquired and segmented before surgery to create baseline anatomical models. This preliminary processing establishes reference frameworks that accelerate intraoperative navigation and reduce real-time processing requirements
Solution Approach 2:
The system creates registered 3D copies of the surgical site by integrating preoperative imaging data with intraoperative 2D images. These registered representations serve as virtual models that guide surgical instrumentation without requiring continuous processing of raw imaging data
3Reliability
If anatomical structures are segmented and registered in real-time, then reliability is improved, but device complexity increases
Solution Approach 1:
The system provides real-time feedback by registering intraoperative 2D images with preoperative 3D datasets and displaying registered representations that show instrument positions relative to segmented anatomical structures. This feedback loop enhances surgical reliability through continuous verification of instrument placement
Solution Approach 2:
A computing device serves as an intermediary that integrates preoperative 3D image datasets with intraoperative 2D images, performs segmentation and registration, and generates registered representations for display. This intermediary processing layer manages complexity by centralizing computational tasks
Data Source
AI summary
A method includes receiving a three-dimensional image dataset of a surgical site of a patient. The method also includes segmenting one or more anatomical features of the surgical site based on the three-dimensional image dataset. The method also includes receiving a two-dimensional image of the surgical site of the patient and registering the two-dimensional image to an image from the three-dimensional image dataset. The method also includes displaying a two-dimensional representation of the segmented one or more anatomical features based on the registered two-dimensional image and the image from the three-dimensional image dataset.