Enhanced Endoscopic Imaging System with Adaptive Illumination and Machine Learning

An improved endoscopic imaging system that dynamically adjusts illumination intensity and image sensor gain for better image quality, and incorporates machine learning algorithms to detect structures and generate examination reports.

The original patent for endoscopic imaging systems has limitations in terms of image quality and manual detection of structures. This new inventive concept addresses these limitations by introducing adaptive illumination and machine learning capabilities to improve the efficiency and accuracy of endoscopic examinations.

The enhanced endoscopic imaging system consists of a video endoscope with a CMOS image sensor, a light source capable of generating white light and special light, and a controller. The controller is adapted to adjust the illumination intensity of the special light based on the distance of the video endoscope from the examination surroundings, ensuring optimal image quality. Additionally, the system automatically adjusts the gain of the CMOS image sensor based on the brightness of the captured images. The controller is also capable of detecting the presence of a structure having a predefined characteristic in the white light images and automatically switching to a special light illumination mode. Furthermore, the system incorporates machine learning algorithms to detect the presence of structures and generate a report of the examination results.

The new inventive concept introduces adaptive illumination and machine learning capabilities, which are not present in the original patent. These features provide a significant improvement in image quality, detection accuracy, and examination efficiency, making the new concept novel and non-obvious.

Alternative embodiments of the inventive concept could include using different types of image sensors, such as CCD or sCMOS, or incorporating additional sensors for detecting other parameters like temperature or pressure. The machine learning algorithms could also be trained on different datasets or used in conjunction with other AI techniques.

The enhanced endoscopic imaging system has significant commercial potential in the medical industry, particularly in the fields of gastroenterology, urology, and pulmonology. The system's improved image quality and automated detection capabilities could increase the efficiency and accuracy of endoscopic examinations, leading to better patient outcomes and reduced healthcare costs.