Article Dans Une Revue BioMedical Engineering OnLine Année : 2018

Variational based smoke removal in laparoscopic images

Résumé

Background: In laparoscopic surgery, image quality can be severely degraded by surgical smoke, which not only introduces errors for the image processing algorithms (used in image guided surgery), but also reduces the visibility of the observed organs and tissues. To overcome these drawbacks, this work aims to remove smoke in laparoscopic images using an image preprocessing method based on a variational approach. Methods: In this paper, we present the physical smoke model where the degraded image is separated into two parts: direct attenuation and smoke veil and propose an efficient variational-based desmoking method for laparoscopic images. To estimate the smoke veil, the proposed method relies on the observation that smoke veil has low contrast and low inter-channel differences. A cost function is defined based on this prior knowledge and is solved using an augmented Lagrangian method. The obtained smoke veil is then subtracted from the original degraded image, resulting in the direct attenuation part. Finally, the smoke free image is computed using a linear intensity transformation of the direct attenuation part.

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hal-04069244 , version 1 (03-02-2024)

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Congcong Wang, Faouzi Alaya Cheikh, Mounir Kaaniche, Azeddine Beghdadi, Ole Jacob Elle. Variational based smoke removal in laparoscopic images. BioMedical Engineering OnLine, 2018, 17 (1), pp.139. ⟨10.1186/s12938-018-0590-5⟩. ⟨hal-04069244⟩
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