Automated 3D Bone Deformation Analysis from CT Scans
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Solution Overview
Problem
Current methods for characterizing bone deformation, particularly in the hip joint, are laborious, inaccurate, and lack reproducibility due to reliance on manual processing of 2D images from 3D medical scans, which is inadequate for precise surgical planning in cases like Femoro Acetabular Impingement (FAI).
Innovation Solution
An automated method and system for determining 3D parameters characterizing bump deformations at the head-neck junction of bones from 3D medical images, involving the construction of a 3D surface model, fitting a sphere to the femoral head, determining the neck axis, establishing a clock face reference, and calculating a 3D curve to quantify the deformation, using algorithms and image processing techniques to minimize user interaction and ensure precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual processing of 2D images is used to characterize bone deformation, then the method is simple to operate, but the measurement precision and reproducibility deteriorate
Solution Approach 1:
The patent replaces manual mechanical processing of 2D images with an automated computer-based system that processes 3D CT scan data. The system automatically reconstructs 3D models of the femoral head and neck, calculates geometric parameters (alpha angle, beta angle, gamma angle), and generates diagnostic reports without requiring manual measurement by radiologists. This substitution of manual mechanical operations with automated computational algorithms significantly improves measurement precision and reproducibility while maintaining ease of operation through user-friendly interfaces.
Solution Approach 2:
The patent transitions from manual measurement of 2D image slices to automated analysis of 3D volumetric data. By reconstructing three-dimensional models from CT scan data and calculating geometric parameters in 3D space, the system captures the full spatial complexity of bone deformities that cannot be adequately represented in 2D projections. This dimensional transition enables more accurate characterization of complex deformities while maintaining operational simplicity through automated processing.
2Device complexity
If manual identification of neck axis and fitting of circles in 2D images is performed, then the device complexity is low, but the measurement precision and reproducibility deteriorate
Solution Approach 1:
The patent replaces manual identification of anatomical structures and geometric fitting operations with automated computer algorithms. The system automatically identifies the femoral neck axis, fits circles to the femoral head contour, and calculates angular parameters from 3D model data. This automated approach eliminates inter-observer variability and improves measurement precision without requiring complex manual measurement tools or procedures.
Solution Approach 2:
The system performs self-service processing by automatically extracting and measuring geometric parameters from 3D models without requiring manual intervention. The automated algorithms independently complete the entire measurement process from data acquisition to result generation, eliminating the need for manual measurement techniques and improving both precision and reproducibility.
3Loss of time
If 2D image slices are used to characterize bone deformation, then the processing time is short, but the measurement precision deteriorates due to loss of 3D information
Solution Approach 1:
The patent utilizes three-dimensional volumetric data from CT scans to reconstruct accurate 3D models of the femoral head and neck. By working in 3D space rather than restricting analysis to 2D slices, the system preserves complete spatial information about bone geometry and deformation. This dimensional approach enables precise measurement of complex deformities while maintaining reasonable processing times through automated algorithms that efficiently handle 3D data.
Solution Approach 2:
The system performs preliminary reconstruction of 3D models from CT scan data before conducting measurements. This pre-processing step creates accurate three-dimensional representations that can be efficiently analyzed by automated algorithms. By preparing the data in advance in a structured 3D format, the system optimizes both measurement precision and processing efficiency, avoiding the need for time-consuming manual analysis of complex 3D geometries.
Data Source
AI summary
The invention relates to a method for automatically determining, on a bone comprising a head portion contiguous to a neck portion, parameters for characterizing a bump deformation on the head-neck junction of the bone from acquired 3D medical image, the method comprising the following steps: i) constructing a 3D surface model of the bone; ii) fitting a sphere on the spherical portion of the head of the bone; iii) determining a neck axis characterizing the neck portion of the bone; iv) determining from the fitted sphere and the neck axis, a clock face referential on the head of the bone rotating around the neck axis; v) determining a 3D curve on the 3D surface model characterizing the head-neck junction of the bone; vi) determining, from the 3D curve, the summit of the bump deformation of the head-neck junction of the bone; vii) determining, from said summit of the bump deformation, first and a second parameters (α3D, iMax) characterizing the maximum bump deformation of the head-neck junction of the bone.