Wang Q, Tao P, Yuan B, et al. Vessel enhancement of endoscopic image based on multi-color space[J]. Opto-Electron Eng, 2020, 47(1): 190268. doi: 10.12086/oee.2020.190268
Citation: Wang Q, Tao P, Yuan B, et al. Vessel enhancement of endoscopic image based on multi-color space[J]. Opto-Electron Eng, 2020, 47(1): 190268. doi: 10.12086/oee.2020.190268

Vessel enhancement of endoscopic image based on multi-color space

    Fund Project: Supported by National Research and Development Plan (2017YFC0109603), Research and Development Plan of Zhejiang (2018C03064), Special Fund for Basic Scientific Research in Central Colleges and Universities (2019FZA5016)
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  • In order to improve the contrast between the blood vessels and tissues of the images obtained by medical electronic endoscopes, a vessel enhancement method of non-linear contrast stretching in multi-color space is proposed according to the characteristics of endoscopic vascular images. Firstly, in RGB color space, stretching contrast adaptively of the green (G) component by using the nonlinear mapping function. Secondly, adjusting the gray value of the two components of red (R) and blue (B) according to the stretching result of the G component. Thirdly, converting the image to HSV color space, and stretching contrast adaptively of the saturation (S) component of the image. Finally, converting the image back to RGB color space, and the purpose of vessel enhancement is achieved. In this paper, the proposed algorithm is used to process several electronic endoscopic images with different contrast and brightness. The results show that the algorithm has better enhancement effect on small blood vessels which are not obvious in original features. Comparing to other enhancement methods, the detail variance (DV) of the enhanced image is significantly great. The algorithm is embedded in a resolution of 1280×800 endoscopic software, 26 frames can be processed per second.
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  • Overview: The vessel enhancement for medical endoscopic images can provide more details of blood vessels, which is useful for assisting doctors in diagnosis. An enhancement method based on multi-color spatial nonlinear contrast stretching is proposed in the present study, which is able to effectively perform vessel enhancement for endoscopic images in real time.

    In the proposed method, the contrast stretching for enhancement is successively carried out for the G (Green) component in RGB color space and the S (Saturation) component in HSV color space. Since the details in G component are usually clearer than those in R (Red) and B (Blue) component for the endoscopic tissue images, the contrast stretching for G component only can more effectively enhance the vessels in the tissue. And the contrast stretch for S component can make the color of vessels brighter than that of tissue, which is suitable to the human visual system.

    First, the G component is mapped by a nonlinear mode for contrast stretching. The mapping parameter is determined by that the value with maximum contrast stretching effect in the nonlinear mode is equal to the average value of G component of image. Then, the color space of image is converted from RGB to HSV and the S component is mapped by a nonlinear mode same to the G component. Similarly, the mapping parameter of S component is determined by that the value with maximum contrast stretching effect is equal to the average value of S component of image. Finally, the enhanced image is obtained by converting the HSV data with enhanced S component to RGB color space.

    The above algorithm was implemented by a C# program and its enhancement effect was tested by multiple endoscopic vessel images. The experiment results show that even very small vessels which are almost invisible in the original images can be seen in the enhanced images under the suitable mapping parameter determined by the proposed method. The enhanced images are also compared with those obtained by FICE and Spectral-B, which are normal enhancement methods in their respective endoscopes. It is showed that only our enhancement images have consistent color tone with the original images and the DVs (detail variances) of our enhancement images are significantly larger than those obtained by FICE or Spectral-B. The enhancement algorithm was embedded in the program for an endoscope with a resolution of 1280 pixels×800 pixels, and the video speed with enhancement effect was tested to reach 26 fps on a computer with the 2.7 GHz CPU and 3.2 G memory.

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