Surgical Planning System for Bone Reconstruction Using 3D Segmentation
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Solution Overview
Problem
Current surgical planning systems for reconstructing missing or damaged bone parts are computationally intensive, lack precision, and are heavily dependent on the surgeon's experience, leading to inefficiencies and increased risks of bone necrosis due to inadequate metabolism.
Innovation Solution
A surgical planning system that processes 3D image data to distinguish osseous and soft tissue structures, generates 3D target curves, and segments donor area data to adapt to target surfaces, allowing for automated planning and consideration of anatomical curves, vascular systems, and soft tissues, thereby simplifying the reconstruction process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional surgical planning methods using pre-bent plates or cutting templates are used, then surgical guidance is provided, but the process is time-consuming and relatively imprecise
Solution Approach 1:
The patent creates virtual 3D copies of the patient's anatomy from CT/MRI data, allowing precise digital planning without physical templates. The segmentation algorithm generates digital models that can be manipulated and measured accurately, eliminating the need for time-consuming physical template fabrication and fitting while achieving superior precision.
Solution Approach 2:
The patent replaces mechanical cutting templates and pre-bent plates with computer-based segmentation algorithms and virtual reality visualization. The automated 3D surface generation and curve adaptation occur through software processing rather than manual mechanical operations, dramatically reducing planning time while maintaining or improving precision through algorithmic accuracy.
2Ease of operation
If software approaches with step-by-step guidance are used, then surgical assistance is provided, but the expense is enormous and the process requires a clinically trained engineer
Solution Approach 1:
The patent implements automated segmentation algorithms that independently process 3D image data without requiring manual intervention by trained engineers. The system automatically distinguishes bone from soft tissue, generates surface models, and creates surgical guides, making the complex process accessible to surgeons without requiring specialized engineering expertise or expensive manual software systems.
Solution Approach 2:
The patent transforms complex medical imaging data into simplified 3D surface representations through automated parameter extraction. By changing the data representation from raw volumetric images to segmented surface models with key anatomical features, the system reduces complexity while preserving essential surgical information, making it usable by standard surgical teams without expensive specialized software.
3Manufacturing precision
If a plurality of bone incisions are made to achieve better reconstruction outcome, then aesthetic and functional results improve, but the likelihood of bone necrosis due to inadequate metabolism increases
Solution Approach 1:
The patent applies segmentation algorithms that identify and preserve critical anatomical structures such as vascular channels and nutrient foramina in the 3D models. By locally analyzing the bone architecture and marking these sensitive areas, the system enables surgeons to plan incisions that achieve precise reconstruction while avoiding regions that would compromise blood supply and cause necrosis.
Solution Approach 2:
The patent provides visual feedback through 3D surface displays that show the planned segmentation and reconstruction geometry before surgery. The system allows surgeons to review and adjust the virtual incision lines and segment arrangements, providing immediate visual feedback on how different planning options affect both reconstruction quality and bone viability, enabling optimization of the surgical plan to balance aesthetic/functional outcomes with necrosis prevention.
Data Source
AI summary
A surgical planning system for the reconstruction of missing or damaged bone parts comprises processing circuitry for receiving 3D image data regarding at least one osseous donor area, processing the 3D image data into structured 3D image data where osseous portions are distinguished from soft tissues and/or vascular systems, reading in of 3D target data regarding a missing or damaged bone part, obtaining one or more 3D target curves in relation to the 3D target data and the 3D image data of the at least one osseous donor area, and segmenting the structured 3D image data with the osseous portions of the osseous donor area into segments, where the segments within the structured 3D image data are determined based on the 3D target data and an adaptation of sections of the one or more 3D target curves.