Medical Image Correction via Computer Analysis Module
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Medical images captured by mobile devices often suffer from flawed photography effects such as glare, reflections, and exposure issues, which can hinder accurate diagnosis and disease state identification.
Innovation Solution
A device and method that utilize a computer analysis and correction module (CACM) to identify and correct flawed photography effects in digital medical images, enhancing the images and generating annotations for cancer identification or other disease states using artificial intelligence mechanisms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a mobile device captures a digital copy of a medical image displayed on a display device, then the medical image can be processed and annotated using AI mechanisms, but flawed photography effects such as glare, reflections, and exposure issues are introduced that hinder accurate diagnosis
Solution Approach 1:
The system performs preliminary actions by capturing multiple images in sequence before final processing. The CACM module analyzes these preliminary captures to identify photography flaws, and the system prepares corrected versions before the actual diagnostic annotation process begins. This preliminary correction of glare, reflections, and exposure issues ensures that the final annotated image is free from capture artifacts.
Solution Approach 2:
The CACM (Computer Analysis and Correction Module) acts as an intermediary between the raw captured image and the AI annotation process. It mediates by analyzing the captured image for photography flaws and generating corrected versions, thereby isolating the diagnostic process from the harmful effects of glare, reflections, and exposure issues while preserving the automated workflow.
2Measurement precision
If multiple images are captured in sequence to identify and correct photography flaws, then the accuracy of medical image analysis is improved, but the time required to process and present the enhanced image increases
Solution Approach 1:
The system performs preliminary analysis of multiple captured images to identify photography flaws such as glare and reflections before the actual diagnostic process. By detecting and correcting these issues in advance using the CACM module, the system ensures high measurement precision in the final annotated image while preparing corrected versions beforehand to minimize processing time during actual diagnosis.
Solution Approach 2:
The system implements feedback mechanisms where the CACM module continuously analyzes captured images, identifies photography flaws, and adjusts correction parameters based on the detected issues. This feedback loop allows the system to optimize the correction process in real-time, improving measurement precision while reducing the time needed for manual intervention and re-capture.
Data Source
AI summary
A device to enhance and present a medical image using a corrective mechanism is described. An image analysis application executed by the device captures a digital copy of the medical image displayed on a display device. A flawed photography effect associated with the digital copy is identified by processing the digital copy. Next, the digital copy is enhanced based on the flawed photography effect. Furthermore, the enhanced digital copy can be processed with an artificial intelligence mechanism to generate an annotation. The annotation is associated with a cancer identification. In addition, the enhanced digital copy and the annotation are displayed.