Portable Cervical Imaging for Automated Lesion Detection
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Solution Overview
Problem
Current cervical cancer detection methods, particularly in low-to-middle income countries, are hindered by expensive equipment, lack of trained professionals, and inadequate imaging technology, leading to higher mortality rates due to undiagnosed cervical cancer.
Innovation Solution
A low-cost, portable Cervitude Imaging System (CIS) device that includes a probe with LEDs for illumination, a camera, and a processor to capture and analyze cervical images, segmenting regions of interest, and transmit data to a host system for lesion detection and classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional colposcopy equipment is used for cervical cancer detection, then imaging quality and lesion detection capability are improved, but device cost and complexity increase significantly
Solution Approach 1:
The patent uses a digital camera to capture optical images of the cervix, creating a digital copy that can be analyzed by image processing algorithms. This replaces the need for complex traditional colposcopy equipment while maintaining diagnostic capability through computational analysis of the captured images
Solution Approach 2:
The patent replaces mechanical/optical magnification systems with digital image capture and computational image processing. The processor analyzes captured images to detect lesions, substituting complex optical mechanisms with electronic and software-based solutions
2Measurement precision
If traditional colposcopy equipment is used for cervical cancer detection, then lesion detection accuracy is improved, but portability and ease of deployment are worsened
Solution Approach 1:
The patent divides the detection system into separate functional components: a portable data capture device with camera and light source, and a separate processor for image analysis. This segmentation enables the capture device to be small and portable while the processing can be performed on connected computing equipment
Solution Approach 2:
By capturing digital images that can be transmitted and analyzed separately, the system allows the physical examination device to remain small and portable while maintaining accurate lesion detection through remote or local image processing
3Measurement precision
If manual image analysis by trained professionals is used, then diagnostic accuracy is improved, but cost and availability in resource-constrained areas are worsened
Solution Approach 1:
The patent implements automated image processing algorithms that can independently analyze captured cervical images and detect lesions without requiring trained professionals to perform manual analysis. This self-service capability enables deployment in areas lacking specialized medical expertise
Solution Approach 2:
The patent replaces human expert analysis with computational image processing algorithms. The processor automatically identifies lesion characteristics from captured images, substituting the need for trained colposcopists with automated electronic analysis
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
Enables early detection of precancerous lesions with high accuracy, reducing the need for trained professionals and lowering costs, making it suitable for resource-constrained areas.
Implementation Method 1
a probe with LEDs for illumination
Data Source
AI summary
A method for automatic, image-based detection of abnormalities in a patient's cervix is disclosed. In an embodiment, a Cervitude Imaging System (CIS) processor of a CIS device illuminates a light source affixed to a distal end of a probe housing, receives cervical image data of the patient from a camera affixed to the distal end of the probe housing, generates a reconstructed image that includes reduced specular reflections, and segments the reconstructed image into at least one region of interest (ROI). The process also includes the CIS processor transmitting the reconstructed image comprising the at least one ROI to at least one of a host system and an input/output device.