Shandong Normal University

Linchuan Nie

Hao Li

Dengwang Li

Jie Xue

Baolong Tian

Bin Jin

Pu Huang

Xiangyu Zhai

Haitao Niu

Yao Cheng

Guangyong Zhang

Disclosed are a method, system, and device for removing smoke from laparoscope images based on a conditional diffusion model. The method includes: segmenting a video of a laparoscopic surgery according to the number of frames to form a data set; performing smoke rendering on the obtained laparoscope smokeless images, and synthesizing paired smoky images to obtain a synthetic data set containing the smokeless images and the smoky images; inputting the smokeless images into the conditional diffusion model for forward noise addition, and continuously adding noise until the smokeless images are completely noised; inputting the smoky images into a smoke sensing module to obtain smoke concentration and position information, then training a neural network, and continuously performing reverse denoising on the completely noised images using the trained neural network until clear smokeless images are outputted; and optimizing a smoke removal model through a multi-loss function fusion strategy.

Method, system, and device for removing smoke from laparoscope images based on conditional diffusion model

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Shandong, China

Linchuan Nie