Bone Contour Detection via Parallel Spatial-Frequency Image Processing
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Solution Overview
Problem
Prior art image segmentation methods for medical imaging, particularly for ultrasound images, are complex and resource-intensive, leading to errors in bone contour detection and requiring cumbersome comparisons of varying image types and qualities, which can be detrimental during surgical procedures.
Innovation Solution
An apparatus and method that apply parallel image processing functions in both spatial and frequency domains to identify bone contours in medical images, creating customized electronic bone structure models for improved surgical assistance by automatically processing images and displaying three-dimensional characteristics in a spatial coordinate system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If prior art image segmentation methods are used to detect bone contours in medical images, then bone structure analysis can be performed, but the methods are complex and consume excessive processing resources and time
Solution Approach 1:
The image processing function is divided into multiple distinct modules: preprocessing module for image enhancement, edge detection module for contour identification, and analysis module for bone structure extraction. Each module performs a specific function, reducing overall system complexity while maintaining detection accuracy through specialized processing at each stage.
Solution Approach 2:
The system performs preliminary image preprocessing operations including noise filtering, contrast enhancement, and normalization before main contour detection. This preliminary preparation simplifies subsequent processing steps and reduces the computational burden during actual bone contour analysis.
2Adaptability or versatility
If prior art image segmentation methods are used to process multiple image types and qualities, then comprehensive bone structure analysis is possible, but errors occur due to image quality variations and require cumbersome comparisons
Solution Approach 1:
The preprocessing module automatically adjusts processing parameters based on detected image characteristics such as noise level, contrast, and resolution. This adaptive parameter adjustment ensures reliable contour detection across different image types and qualities without requiring manual intervention or multiple comparison operations.
3Measurement precision
If prior art methods are used during surgical procedures, then bone structure information can be obtained, but the processing time and resource consumption are detrimental to surgical efficiency
Solution Approach 1:
Bone structure models are generated and stored in advance through preliminary imaging and processing. During surgical procedures, the system rapidly retrieves and displays pre-computed three-dimensional bone models and contour information, eliminating time-consuming processing during the actual surgery while maintaining measurement accuracy.
Solution Approach 2:
The system creates simplified three-dimensional digital models of bone structures that replicate essential anatomical features. These models serve as efficient representations that can be rapidly processed and displayed during surgery, reducing computational requirements compared to processing raw medical images in real-time.
Data Source
AI summary
There is described an apparatus and method for recovering a contour of a bone from an input image of the bone with its surrounding tissues. The method comprises receiving the input image; applying in parallel at least three image processing functions to the input image to obtain at least three resulting images indicative of respective features of the input image, at least one of the at least three image processing functions pertaining to a spatial domain, and at least another one of the at least three image processing functions pertaining to a frequency domain; combining the at least three resulting images together to form a compounded image, the compounded image identifying at least two regions based on the respective features; identifying the contour of the bone based on the at least two regions of the compounded image; and outputting an output image for display, the output image comprising the contour identified.