Capsule Endoscope Image Stitching for Expanded Field of View
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Solution Overview
Problem
The limited resolution and depth of field in images captured by capsule endoscopes make it difficult for physicians to identify specific lesions and assess the overall condition of gastrointestinal mucosa effectively due to the device's size and power consumption constraints.
Innovation Solution
A method for stitching images captured by a capsule endoscope, involving image rectification, circular edge masking, image enhancement, feature point detection and pairing, projective transformation, and fusion to create a comprehensive fused image, utilizing techniques like guided filters, non-rigid dense matching, and Thin Plate Spline deformation for optimal stitching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple images are captured to expand field of view, then observation coverage is improved, but image stitching complexity increases
Solution Approach 1:
The image stitching process is divided into distinct segments: feature point detection, feature point pairing, transformation model calculation, and image fusion. Each segment handles a specific aspect of the stitching process, making the overall complex task manageable and systematic.
Solution Approach 2:
Feature points are detected and paired in advance before the actual image stitching operation. Transformation models are pre-calculated based on these feature points, allowing the final stitching process to proceed efficiently with predetermined transformation parameters.
2Measurement precision
If image resolution is increased to improve lesion identification, then diagnostic accuracy is improved, but capsule endoscope size and power consumption increase
Solution Approach 1:
Multiple low-resolution images captured by the small capsule endoscope are merged through stitching to create a single high-resolution composite image. This combines the computational advantage of small sensor size with the diagnostic benefit of high resolution in the final image.
Solution Approach 2:
Instead of increasing resolution in the spatial dimension within the capsule, the solution transitions to the temporal dimension by capturing multiple images over time and combining them computationally to achieve high resolution in the final stitched image.
3Loss of information
If multiple images are stitched to show overall gastrointestinal condition, then diagnostic comprehensiveness is improved, but processing time increases
Solution Approach 1:
Feature points are detected and paired in advance before the actual image stitching operation. Transformation models are pre-calculated based on these feature points, allowing the final stitching process to proceed efficiently with predetermined transformation parameters rather than calculating everything in real-time.
Solution Approach 2:
The patent replaces complex real-time mechanical image processing with pre-calculated transformation models and feature point data, reducing the computational burden during actual stitching operations and thereby reducing processing time.
Data Source
AI summary
A method for stitching images of a capsule endoscope, an electronic device, and a readable storage medium are provided. The method comprises: performing image rectification and circular edge masking on original images to form pre-processed images, and performing image enhancement (S1); completing detection and pairing of feature points (S2); calculating a transformation model of all pre-processed images to a same optimal plane according to a set of the feature points (S3); performing projective transformation for each enhanced image to a same coordinate system (S4); and stitching images according to an obtained sequence to form a fused image for output (S5), thus expanding the field of view of a single image of the capsule endoscope.