Title:
深層学習に基づく気管挿管位置決め方法、装置及び記憶媒体
Document Type and Number:
Japanese Patent JP7347738
Kind Code:
B2
Abstract:
The disclosure relates to a tracheal intubation positioning method and device based on deep learning, and a storage medium. The method includes: constructing a YOLOv3 network based on dilated convolution and feature map fusion, and extracting feature information of an image through the trained YOLOv3 network to acquire first target information; determining second target information by utilizing a vectorized positioning mode according to carbon dioxide concentration differences detected by sensors; and fusing the first target information and the second target information to acquire a final target position. According to the disclosure, the tracheal orifice and the esophageal orifice can be rapidly detected in real time. Using the stepsConstructing a YOLOv3 network based on dilated convolution and feature map fusion, and extracting feature information of an image through the trained YOLOv3 network to acquire first target information;Determining second target information by utilizing a vectorized positioning mode according to carbon dioxide concentration differences detected by sensors;Fusing the first target information and the second target information to acquire a final target position.
Inventors:
Ginger rainbow
Summer
instinct
Zhang Rong-fu
Lifeng
Xu Tenyi
Summer
instinct
Zhang Rong-fu
Lifeng
Xu Tenyi
Application Number:
JP2022014750A
Publication Date:
September 20, 2023
Filing Date:
February 02, 2022
Export Citation:
Assignee:
Ninth People's Clinic, Shanghai Jiaotong University School of Medicine
International Classes:
G06T7/00; A61B34/10
Foreign References:
| US20150059736 |
Attorney, Agent or Firm:
Tomoo Tanaka
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