Surgical tool tracking system based on convolutional neural network and long-term and short-term memory network

A technology of convolutional neural network and long-term and short-term memory, which is applied in the field of surgical tool tracking system based on convolutional neural network and long-term and short-term memory network, can solve problems such as high computing power and computer hardware level requirements, and meet real-time detection requirements. , reduce the operation time of the program, good real-time performance

Pending Publication Date: 2020-12-04
SHANDONG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The inventor found that using a deep learning-based target detection algorithm for surgical tr

Method used

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  • Surgical tool tracking system based on convolutional neural network and long-term and short-term memory network
  • Surgical tool tracking system based on convolutional neural network and long-term and short-term memory network

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Experimental program
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Embodiment 1

[0029] This embodiment provides a surgical tool tracking system based on a convolutional neural network and a long short-term memory network;

[0030] Surgical tool tracking system based on convolutional neural network and long short-term memory network, including:

[0031] The acquisition module is configured to: acquire a video stream of the working state of the endoscopic surgical tool, and extract two adjacent frames of images from the video stream; the two adjacent frames of images are respectively: a first frame image and a second frame image; Mark the surgical tool bounding box of the first frame image;

[0032] A feature extraction module configured to: perform feature extraction on the first frame image and the second frame image to obtain the spatial motion feature of the surgical tool;

[0033] A feature fusion module configured to: input the spatial motion feature of the surgical tool into the first LSTM model, and the first LSTM model processes the spatial motion...

Embodiment 2

[0102] This embodiment also provides an electronic device, including: one or more processors, one or more memories, and one or more computer programs; wherein, the processor is connected to the memory, and the one or more computer programs are programmed Stored in the memory, when the electronic device is running, the processor executes one or more computer programs stored in the memory, so that the electronic device executes the functions of the system described in Embodiment 1 above.

[0103] It should be understood that in this embodiment, the processor can be a central processing unit CPU, and the processor can also be other general-purpose processors, digital signal processors DSP, application specific integrated circuits ASIC, off-the-shelf programmable gate array FPGA or other programmable logic devices , discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor, or the processor may be any conventi...

Embodiment 3

[0109] This embodiment also provides a computer-readable storage medium for storing computer instructions. When the computer instructions are executed by a processor, the functions of the system described in Embodiment 1 are completed.

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Abstract

The invention discloses a surgical tool tracking system based on a convolutional neural network and a long-term and short-term memory network, and the system comprises an obtaining module which obtains a working state video stream of an endoscopic surgical tool, extracts two adjacent frames of images from the video stream, and marks the surgical tool bounding box of the first frame of image; a feature extraction module used for carrying out feature extraction on the first frame image and the second frame image to obtain spatial motion features of the surgical tool; a feature fusion module inputting the features into a first LSTM model, and the first LSTM model processing the spatial motion features of the surgical tool to obtain a first feature vector; a feature recognition module used forfusing the features and the first feature vector and then inputting the fused features and the first feature vector into a second LSTM model, and the second LSTM model outputting a second feature vector, inputting the second feature vector into a full connection layer to obtain a final feature vector, and obtaining a bounding box of the surgical tool of the second frame image.

Description

technical field [0001] The present application relates to the technical field of endoscopic surgical tool tracking, in particular to a surgical tool tracking system based on a convolutional neural network and a long short-term memory network. Background technique [0002] The statements in this section merely mention the background art related to this application, and do not necessarily constitute the prior art. [0003] Computer-assisted surgery is a new interdisciplinary research field integrating medicine, mechanics, materials science, computer technology, information management, communication technology and many other disciplines. Its purpose is to use computer technology (mainly computer graphics technology) to solve various problems involved in medical surgery, including surgical planning, surgical navigation, and auxiliary treatment planning. [0004] Surgical tool tracking algorithm: It uses surgical tool tracking technology and deep learning technology to analyze v...

Claims

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Application Information

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IPC IPC(8): G06T7/246G16H40/20G06N3/04G06N3/08
CPCG06T7/246G16H40/20G06T2207/10016G06T2207/20084G06T2207/20081
Inventor 赵子健杨煜
Owner SHANDONG UNIV
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