Shandong Normal University

Other

Dengwang Li

Baolong Tian

Bin Jin

Xiangyu Zhai

Pu Huang

Jie Xue

Hao Li

Changming Gu

Yueqiang Liang

Guangyong Zhang

Chuanyi Zhang

Xueyao Liu

Tingxuan Hong

Hua Lu

Linchuan Nie

Haitao Niu

Yao Cheng

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

A laparoscopic image smoke removal method based on a generative adversarial network, and belongs to the technical field of computer vision. The method includes: processing a laparoscopic image sample to be processed using a smoke mask segmentation network to acquire a smoke mask image; inputting the laparoscopic image sample to be processed and the smoke mask image into a smoke removal network, and extracting features of the laparoscopic image sample to be processed using a multi-level smoke feature extractor to acquire a light smoke feature vector and a heavy smoke feature vector; and acquiring, according to the light smoke feature vector, the heavy smoke feature vector and the smoke mask image, a smoke-free laparoscopic image by filtering out smoke information and maintaining a laparoscopic image by using a mask shielding effect. The method has the technical effects of robustness and ability of being embedded into a laparoscopic device for use.

Laparoscopic image smoke removal method based on generative adversarial network

The present invention discloses a personal health record system with a process decision support function. By constructing a personal health record system with separated characteristic data extraction and characteristic data analysis, characteristic data that meets analysis requirements is expected to be rapidly obtained. A statistics query interface based on characteristic data and time logic is provided, and decision support for users is completed through steps such as characteristic matching, process classification and statistics evaluation, and process recommendation, so as to make medical big data better execute high-level information analysis and decision support functions.

Personal health record system with process decision support function

Growing community of inventors

Shandong, China

Dengwang Li