Anatomical Label Positioning in 3D Medical Imaging
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Solution Overview
Problem
Current medical imaging technologies face challenges in accurately and efficiently recognizing anatomical structures within medical images, particularly due to improper placement of vertebral labels which can obscure or confuse diagnostic information.
Innovation Solution
A framework for visualizing anatomical labels in three-dimensional medical images that localizes structures of interest and positions labels outside the structures of interest, using a selected positioning technique based on the view type of the visualization plane, ensuring accurate and unambiguous labeling without obscuring critical information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If anatomical labels are placed directly on or near anatomical structures in medical images, then label visibility and association are improved, but image interpretation is adversely affected due to label occlusion and confusion
Solution Approach 1:
The patent applies dimensionality change by moving labels from a two-dimensional image plane to a three-dimensional space around the anatomical structures. Labels are positioned in 3D space at calculated offsets from the structure centroids, allowing them to be projected onto the 2D image plane without overlapping the structures themselves. This resolves the contradiction by using the third dimension (depth) to separate labels from structures while maintaining visual association.
Solution Approach 2:
The patent introduces an intermediary positioning system that calculates optimal label locations based on structure geometry, view orientation, and spatial relationships. This intermediary layer (the positioning algorithm) mediates between the need for visible labels and the need to preserve image interpretability, automatically determining positions that satisfy both requirements without manual intervention.
2Productivity
If automated vertebral labeling is implemented to improve diagnostic efficiency, then recognition speed is improved, but label placement accuracy deteriorates leading to improper visualization
Solution Approach 1:
The patent applies preliminary action by pre-calculating optimal label positions based on the 3D geometry of anatomical structures and the current view orientation before rendering the image. The system determines structure centroids, calculates offset positions, and establishes positioning rules in advance, so that when automated labeling is performed, labels are immediately placed at correct locations without requiring post-processing or manual adjustment.
Solution Approach 2:
The patent implements dynamics by making label positions adaptive to the current view orientation and camera angle. As the user rotates or changes the visualization plane, the label positions are dynamically recalculated to maintain optimal placement relative to the structures. This dynamic positioning ensures accuracy across different viewing conditions while maintaining automated labeling efficiency.
3Manufacturing precision
If multiple positioning techniques are used for different view types to improve label placement accuracy, then label visualization quality is improved, but system complexity increases
Solution Approach 1:
The patent applies universality by creating a unified positioning framework that handles multiple view types (axial, sagittal, coronal, and oblique) through a single set of geometric principles. The system uses view-type-agnostic calculations based on structure centroids and relative offsets, with automatic adaptation to different orientations. This universal approach achieves high placement accuracy across all view types without requiring separate complex positioning systems for each view.
Solution Approach 2:
The patent uses parameter changes by adjusting label position parameters (offset distances, angles, and coordinates) based on the detected view type and orientation. Rather than using fundamentally different positioning methods for each view, the system modifies numerical parameters within a unified mathematical framework, allowing accurate label placement across diverse viewing conditions while maintaining system simplicity.
Data Source
AI summary
A framework for visualization is described herein. In accordance with one implementation, one or more structures of interest are localized in a three-dimensional image. A position of an anatomical label may be determined using a positioning technique that is selected according to a view type of a visualization plane through the image, wherein the position of the anatomical label is outside the one or more structures of interest. The anatomical label may then be displayed at the determined position in the visualization plane.