Automated 3D Head Shape Image Orientation and Cropping
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Solution Overview
Problem
Existing cranial remodeling systems require manual operator intervention for data reorientation and cropping, leading to inefficiencies and inconsistencies in processing three-dimensional head shape data, which can be improved with an automated system that is operator-independent.
Innovation Solution
An automated system and method that orients and crops three-dimensional digital image representations of a subject's head shape using a database library of reference images, employing support vector machines and alignment algorithms to produce a modified head shape representation, allowing for direct image capture and processing without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual operator intervention is used for data reorientation and cropping, then flexibility in handling individual subjects is maintained, but processing efficiency and consistency deteriorate
Solution Approach 1:
The system performs self-service by automatically reorienting and cropping three-dimensional head shape data without requiring manual operator intervention. The automated algorithm processes the data independently, selecting and extracting the necessary portions of the scanned data to create standardized representations, thereby eliminating the need for operator dependency while maintaining processing efficiency and consistency.
2Extent of automation
If automated processing is implemented, then operator dependency is reduced, but handling of clinical adaptations and individual variations becomes challenging
Solution Approach 1:
The system addresses clinical adaptations and individual variations by dynamically adjusting processing parameters such as orientation angles, cropping dimensions, and selection criteria. The automated algorithm modifies these parameters based on the specific characteristics of each subject's head shape, allowing the system to adapt to different clinical scenarios and individual anatomical variations while maintaining operator independence.
Data Source
AI summary
A method for processing digital image representations representative of a subject head shape comprises: providing a database library of a first plurality of first digital image representations of subject head shapes captured directly from corresponding subjects, and a second plurality of second digital image representations of corresponding modified head shapes. The method includes proving a support vector machine and utilizing the database library plurality of said first and second digital image representation to train the support vector machine to operate on new digital image representations. The method further includes receiving a new digital image representation of a subject head shape captured directly from a new subject; and operating the support vector machine such that the support vector machine operates on the new first digital image representation to generate a corresponding new second digital image representation that replicates a corresponding modified head shape.