Medical image three-dimensional film reading and surgery guiding system based on artificial intelligence recommending algorithm

Abstract

The invention discloses a medical image three-dimensional film reading and surgery guiding system based on an artificial intelligence recommending algorithm. The system comprises a balanced load, a web server cluster terminal, a database server terminal, a distributed storage terminal, a distributed calculation cluster, a data acquisition terminal and a film reading and surgery planning terminal.The balanced load is connected with the data acquisition terminal, the film reading and surgery planning terminal and the web server cluster terminal through Internet. When a user uploads data to theserver cluster terminal through the data acquisition terminal, the balanced load detects and distributes a task to an idle server in the web server cluster. When the user calls the three-dimensional data by means of the film reading and surgery planning terminal, the balanced load performs detection and distributes a task to the idle server in the web server cluster. The medical image three-dimensional film reading and surgery guiding system has advantages of supplying previous successful cases as references for clinical surgery guidance, improving convenience and accuracy in searching similarcases, realizing higher speed and more comprehensive performance, and realizing better use prospect.

Description

technical field [0001] The invention belongs to the field of computer technology, and specifically relates to a three-dimensional medical image reading and operation guidance system based on an artificial intelligence recommendation algorithm. Background technique [0002] At present, the recommendation algorithm mainly adopts the recommendation algorithm based on collaborative filtering. The collaborative filtering algorithm is mainly realized by predicting the rating of unrated items. This algorithm is mainly divided into three steps: 1. Score marking, which can be divided into explicit There are two types of scoring and invisible scoring. Explicit scoring is to directly score the case information, and invisible scoring is to score the case information through the evaluation model. 2. Neighbor selection, select several items that are most similar to the current case according to the score, 3. Generate recommendations, push the results of neighbor selection, and pass Addin...

AI Technical Summary

Problems solved by technology

Explicit scoring is to directly score the case information, and invisible scoring is to score the case information through the evaluation model. 2. Neighbor selection, select several items that are most similar to the current case according to the score, 3. Generate recommendations, push the results of neighbor selection, and pass Adding the recommendation algorithm to the medical image reading system will make it easier, faster, more comprehensive and more accurate for doctors to obtain previous successful cases similar to the current case for reference and planning of surgery, or to find similar cases for academic use Research, etc. With the wide application of 3D reconstruction technology in the medical field, more and more 3D reconstruction data are included in the database; there are certain disadvantages in the use of existing planning systems, and doctors plan operations based on 3D reconstruction images. In this case, it is not possible to obtain and refer to the data of similar cases that have been successful in the past, which will be conducive to the smooth progress of the entire surgical process, and it is impossible to create a system that can push similar cases to doctors for reference, which needs further improvement. It has brought a certain impact. Therefore, we propose a 3D medical image reading and surgical guidance system based on artificial intelligence recommendation algorithm

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