3D Anatomical Feature Detection Using Dual-Process Segmentation
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Solution Overview
Problem
Identifying anatomical features from pre-operative images, such as CT scans or MRI, can be difficult and time-consuming for surgeons, hindering the planning of surgical procedures.
Innovation Solution
A method and system that access a three-dimensional (3D) model of an anatomical structure to detect single-layer and non-single-layer anatomical features by generating probability maps and meshes, allowing for accurate visualization and planning of surgical procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual identification of anatomical features from pre-operative images is used, then measurement precision can be achieved, but loss of time increases significantly
Solution Approach 1:
The patent replaces the manual mechanical process of anatomical feature identification with an automated computer-based detection system. The system uses algorithms to automatically identify anatomical features from pre-operative images, substituting the surgeon's manual analysis with computational processing that is both accurate and time-efficient.
Solution Approach 2:
The patent performs preliminary detection and identification of anatomical features before the surgical procedure begins. By pre-processing the images and identifying features in advance, the system prepares the surgical plan ahead of time, reducing the time required during the actual surgical planning phase while maintaining high identification accuracy.
2Productivity
If automated detection processes are applied to 3D models, then productivity increases, but device complexity increases
Solution Approach 1:
The patent divides the complex task of anatomical feature detection into separate specialized modules: one module detects single-layer anatomical features while another detects non-single-layer features. This segmentation allows each module to be optimized for its specific function, improving overall detection efficiency while managing system complexity through modular design.
Solution Approach 2:
The patent creates a universal detection system that can handle multiple types of anatomical features (both single-layer and non-single-layer) using a unified platform. This multi-functional approach increases productivity by detecting various feature types through a single system rather than requiring separate specialized systems for each feature type.
3Measurement precision
If multiple detection processes are used for different anatomical features, then measurement precision is maintained, but device complexity increases
Solution Approach 1:
The patent implements separate detection processes tailored for different anatomical feature types - one process for single-layer features and another for non-single-layer features. Each process is optimized for its specific target, maintaining high measurement precision for each feature type while the overall system manages complexity through this structured division of detection tasks.
Data Source
AI summary
An exemplary system accesses a three-dimensional (3D) model of an anatomical structure, applies a first detection process to the 3D model to detect a single-layer anatomical feature in the anatomical structure, applies a second detection process, different from the first detection process, to the 3D model to detect a non-single-layer anatomical feature in the anatomical structure, and provides a representation of the anatomical structure based on the 3D model, the detected single-layer anatomical structure, and the detected non-single-layer anatomical structure. In some implementations, the representation of the anatomical structure and a representation of a potential path to be traversed by a medical instrument in the anatomical structure are displayed.