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Proceedings Paper

Chromaticity based smoke removal in endoscopic images
Author(s): Kevin Tchaka; Vijay M. Pawar; Danail Stoyanov
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Paper Abstract

In minimally invasive surgery, image quality is a critical pre-requisite to ensure a surgeons ability to perform a procedure. In endoscopic procedures, image quality can deteriorate for a number of reasons such as fogging due to the temperature gradient after intra-corporeal insertion, lack of focus and due to smoke generated when using electro-cautery to dissect tissues without bleeding. In this paper we investigate the use of vision processing techniques to remove surgical smoke and improve the clarity of the image. We model the image formation process by introducing a haze medium to account for the degradation of visibility. For simplicity and computational efficiency we use an adapted dark-channel prior method combined with histogram equalization to remove smoke artifacts to recover the radiance image and enhance the contrast and brightness of the final result. Our initial results on images from robotic assisted procedures are promising and show that the proposed approach may be used to enhance image quality during surgery without additional suction devices. In addition, the processing pipeline may be used as an important part of a robust surgical vision pipeline that can continue working in the presence of smoke.

Paper Details

Date Published: 24 February 2017
PDF: 8 pages
Proc. SPIE 10133, Medical Imaging 2017: Image Processing, 101331M (24 February 2017); doi: 10.1117/12.2254622
Show Author Affiliations
Kevin Tchaka, Univ. College London (United Kingdom)
Vijay M. Pawar, Univ. College London (United Kingdom)
Danail Stoyanov, Univ. College London (United Kingdom)


Published in SPIE Proceedings Vol. 10133:
Medical Imaging 2017: Image Processing
Martin A. Styner; Elsa D. Angelini, Editor(s)

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