Methods, systems and mediums for surgical automation

Patent metadata

Field	Value
Publication number	US-2024071076-A1
Application number	US-202217823950-A
Country	US
Kind code	A1
Filing date	Aug 31, 2022
Priority date	Aug 31, 2022
Publication date	Feb 29, 2024
Grant date	—

Abstract

The present disclosure provides a method for surgical automation. The method may include: obtaining video data generated in a surgical process using a camera; identifying a surgical stage in the surgical process based on the video data; and triggering an activation of a surgical equipment used for a surgical operation and/or providing a guidance of the surgical operation based on the surgical stage.

First claim

What is claimed is:

1 . A method for surgical automation, comprising:
obtaining video data generated in a surgical process using a camera; identifying a surgical stage in the surgical process based on the video data; and triggering an activation of a surgical equipment used for a surgical operation and/or providing a guidance of the surgical operation based on the surgical stage.

2 . The method of claim 1 , wherein identifying a surgical stage in the surgical process includes:
inputting the video data into a recognition model; and determining the surgical stage based on an output of the recognition model, wherein the recognition model is a machine learning model.

3 . The method of claim 2 , wherein an input of the recognition model further includes first auxiliary data related to an acquisition time of the video data, the first auxiliary data including at least one of audio data, physiological monitoring data, and a type of a surgical equipment and usage data of the surgical equipment.

4 . The method of claim 1 , wherein the surgical equipment used for the surgical operation and the guidance of the surgical operation are determined based on target guidance information, and the target guidance information is determined based on the surgical stage.

5 . The method of claim 4 , wherein determining the target guidance information includes:
determining the target guidance information from a plurality of pieces of standard guidance information based on a matching relationship between the surgical stage and reference information corresponding to the plurality of pieces of standard guidance information, wherein the reference information includes a reference surgical stage.

6 . The method of claim 4 , further including:
acquiring execution data, wherein the execution data includes at least one of a video image of an execution process of the surgical operation or usage data of the surgical equipment used for the surgical operation generated in the execution process; determining an execution level of the surgical operation based on a matching relationship between the execution data and the target guidance information; and in response to that the execution level is less than a threshold, providing prompt information.

7 . The method of claim 5 , wherein the reference information further includes at least one of first reference physiological data or first reference case data, and determining target guidance information includes:
obtaining second auxiliary data, the second auxiliary data including at least one of case data of a subject or physiological monitoring data related to an acquisition time of the video data; and determining the target guidance information based on the surgical stage, and a matching relationship between the second auxiliary data and the reference information.

8 . The method of claim 5 , wherein the plurality of pieces of standard guidance information is generated based on historical surgical record, and the historical surgical record meets a predetermined condition.

9 . The method of claim 1 , wherein the surgical stage includes at least one of a normal surgical stage or an abnormal surgical accident.

10 . The method of claim 1 , wherein triggering an activation of a surgical equipment used for a surgical operation includes:
transmitting an activation instruction to the surgical equipment used for the surgical operation, wherein the activation instruction includes one or more parameters.

11 . A system for surgical automation, comprising:
a first acquisition module configured to obtain video data generated in a surgical process using a camera; an identification module configured to identify a surgical stage in the surgical process based on the video data; and a triggering and displaying module configured to trigger an activation of a surgical equipment used for a surgical operation and/or provide a guidance of the surgical operation based on the surgical stage.

12 . The system of claim 11 , wherein the identification module is further configured to:
input the video data into a recognition model; and determine the surgical stage based on an output of the recognition model, wherein the recognition model is a machine learning model.

13 . The system of claim 12 , wherein an input of the recognition model further includes first auxiliary data related to an acquisition time of the video data, the first auxiliary data including at least one of audio data, physiological monitoring data, and a type of a surgical equipment and usage data of the surgical equipment.

14 . The system of claim 11 , wherein the system further includes a first determination module, wherein
the first determination module is configured to determine target guidance information based on the surgical stage; and the triggering and displaying module is further configured to determine the surgical equipment used for the surgical operation and the guidance of the surgical operation based on the target guidance information.

15 . The system of claim 14 , wherein the first determination module is further configured to:
determine the target guidance information from a plurality of pieces of standard guidance information based on a matching relationship between the surgical stage and reference information corresponding to the plurality of pieces of standard guidance information, wherein the reference information includes a reference surgical stage.

16 . The system of claim 14 , further including:
a second acquisition module configured to acquire execution data, wherein the execution data includes at least one of a video image of an execution process of the surgical operation or usage data of the surgical equipment used for the surgical operation generated in the execution process; a second determination module configured to determine an execution level of the surgical operation based on a matching relationship between the execution data and the target guidance information; and a prompt module configured to, in response to that the execution level is less than a threshold, provide prompt information.

17 . The system of claim 15 , wherein the reference information further includes at least one of first reference physiological data or first reference case data, and the first determination module is further configured to:
obtain second auxiliary data, the second auxiliary data including at least one of case data of a subject or physiological monitoring data related to an acquisition time of the video data; and determine the target guidance information based on the surgical stage, and a matching relationship between the second auxiliary data and the reference information.

18 . The system of claim 11 , wherein the surgical stage includes at least one of a normal surgical stage or an abnormal surgical accident.

19 . The system of claim 11 , wherein the triggering and displaying module is further configured to:
transmit an activation instruction to the surgical equipment used for the surgical operation, wherein the activation instruction includes one or more parameters.

20 . A non-transitory computer readable medium storing at least one set of instructions, wherein when executed by at least one processor of a computing device, the at least one set of instructions directs the at least one processor to:
obtain video data generated in a surgical process using a camera; identify a surgical stage in the surgical process based on the video data; and trigger an activation of a surgical equip

Assignees

• Shanghai United Imaging Intelligence Co Ltd

Inventors

• Chen Terrence
• Wu Ziyan
• Sun Shanhui
• Innanje Arun
• Zheng Meng
• Planche Benjamin
• Sharma Abhishek

Classifications

• G06V20/41 Primary

  Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items (segmenting video sequences G06V20/49) · CPC title

• G06V20/44

  Event detection · CPC title

• G06V20/52

  Surveillance or monitoring of activities, e.g. for recognising suspicious objects (recognising microscopic objects G06V20/69) · CPC title

• A61B34/30

  Surgical robots · CPC title

• G06V10/82 Primary

  using neural networks · CPC title