Color-Weighted Polarization Imaging for Laparoscopic Lesion Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current laparoscopic imaging techniques struggle to accurately detect small metastases due to poor sensitivity and specificity, particularly in gastrointestinal and gynecologic malignancies, leading to high false negative rates and delayed treatment options.
Innovation Solution
Employing polarization enhanced light (PEL) imaging with differential weighting of signals in different wavelength channels, utilizing computational models and machine learning to enhance lesion detection and discrimination between benign and malignant lesions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional laparoscopic imaging techniques are used, then the procedure is simple and widely applicable, but the sensitivity to detect small metastases is poor with high false negative rates
Solution Approach 1:
The patent changes the optical parameters of the imaging system by introducing polarization enhancement. The polarization enhanced laparoscope modifies the light polarization state to enhance contrast between normal and abnormal tissues, thereby improving detection sensitivity without requiring complete system redesign
Solution Approach 2:
The patent uses polarization as an intermediary mechanism to bridge the gap between conventional imaging and advanced detection. By introducing polarization modulation and detection, the system enhances tissue contrast through an intermediate optical property that amplifies subtle differences between lesions and normal tissue
2Measurement precision
If polarization enhanced light imaging is implemented, then the optical contrast and lesion visibility are significantly improved, but the device complexity increases due to polarizing structures
Solution Approach 1:
The patent makes the polarizing structures multi-functional by integrating them into the existing laparoscope architecture. The polarization modulation element serves both as a contrast enhancement mechanism and as part of the illumination/detection system, reducing the need for separate dedicated components
Solution Approach 2:
The patent employs dynamic polarization modulation where the polarization state can be adjusted during the procedure. This allows the system to adapt to different tissue types and imaging conditions, providing enhanced contrast when needed while maintaining flexibility in the imaging approach
3Measurement precision
If multi-wavelength polarization enhanced imaging is used, then the discrimination between benign and malignant lesions is enhanced, but the complexity of signal processing and computational models increases
Solution Approach 1:
The patent segments the spectral information into distinct wavelength channels and processes each channel separately through polarization enhancement. This segmentation allows complex multi-wavelength data to be handled through systematic, manageable processing steps for each wavelength band
Solution Approach 2:
The patent incorporates feedback mechanisms where computational models continuously refine their analysis based on the polarization-enhanced imaging data. The system uses feedback from initial imaging to adjust subsequent processing parameters and model predictions, improving lesion discrimination through iterative refinement
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Significantly improves the visibility and accuracy of detecting small metastases by increasing optical contrast, allowing for better staging and treatment selection in cancer patients.
Implementation Method 1
Polarization Enhanced Light (PEL) imaging has been proposed for various biomedical applications as a way of improving surface image contrast. Generally speaking, PEL imaging allows one to distinguish light that has been singly-scattered from a tissue surface from light that has undergone numerous scattering events deeper in tissue
Implementation Method 2
light backscattered from the illuminated target tissue is collected along both the co- and cross-polarized orientations
Data Source
AI summary
Methods for improved imaging of internal tissue structures, such as lesions in the peritoneum, are disclosed employing color-weighted Polarization Enhanced Light (mPEL) imaging. A target tissue can be Illuminated with light of defined polarization at a plurality of wavelengths or wavelength bands. Scattered light from the tissue is collected and its polarization states analyzed and detected either via a polarization sensitive camera or a combination or polarizing filters and a standard camera. Light detected at distinct polarization states and colors is weighted by a factor and combined to yield an image that results in optimized visualization of lesions and/or discrimination of malignant from benign lesions. The factors may be identified based on a combination of Monte Carlo simulations and regression analysis to yield enhanced sensitivity to the tissue scattering power. Alternatively, the factors may be identified through machine learning based optimization algorithms to optimize tissue classification.