ENDOSINO SIEA (Special Imaging Enhancement Algorithms) TECHNOLOGY

Overview: With the development of the minimally invasive surgery, endoscopes have become the necessary medical devices that permit the physicians to examine and cure their patients. However, early diseases are overlooked and tumors still remain in the conventional white light endoscopic surgery. donating companies like ENDOSINO have put many special image enhancement algorithms forward, In order to solve this very important problems.

This paper proposes a blood vessel enhancement algorithm based on the optical spectral absorption characteristics of blood vessels. The contrasts of capillaries and vessels are highlighted by means of reducing the red spectral reflection and increasing the blue and green spectral reflection. The enhancement algorithm includes two aspects: the detail enhancement and the brightness enhancement. Firstly, RGB channels are obtained from the color image and divided into the brightness layer with the high dynamic range and the detail layer with the detail image information through the guided filter. Then, each pixel of the detail image multiplies by an enhanced factor, and the factor of each channel is calculated based on SNR (signal noise ratio). The improvement factor can improve the quality of image enhancement, but excessive factor will amplify the image noise. To get the stretched factor using in brightness layer, each channel is converted from RGB space to CIE space. In this paper, the distance is calculated between the blood vessel and the background in a series of the representative oral vascular biomedical images taken by endoscope (including before and after the image enhancement), and the stretching coefficient is obtained after averaging. After that, the brightness layer is stretched to enhance the GB channel information and to reduce R channel information. Blood vessel information is highlighted because the color of background region turns to green and white, while the color of vessels turns to red and dark. Finally, the detail enhanced image and the brightness-enhanced image are merged to generate a enhanced image.

In order to evaluate the validity of the proposed enhancement method, this paper uses the detail variance-background variance (DV-BV) index and Weber contrast index. For evaluating the enhancement algorithm, the algorithm has been applied to a large number of images captured by endoscopes. The assessment of subjective and objective indicators shows the significant enhancements. Moreover, compared with Karl Stroz’s Spectra B enhancement technology, the method proposed in this paper performs better in image enhancement.

Post time: Jan-20-2020