A multi-target recognition method and system for brachial plexus ultrasound images

A technology of ultrasound images and brachial plexus, which is applied in the field of image recognition, can solve problems such as poor automatic recognition of brachial plexus ultrasound images, achieve the effect of solving blurred segmentation edges, improving network performance, and maintaining consistency

Active Publication Date: 2022-03-01
UNIV OF ELECTRONICS SCI & TECH OF CHINA +1
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  • Abstract
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Problems solved by technology

[0008] In view of the above-mentioned deficiencies in the prior art, the present invention provides a multi-target recognition method and system for brachial plexus ultrasound images to solve the problem of poor automatic recognition of brachial plexus ultrasound images

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  • A multi-target recognition method and system for brachial plexus ultrasound images
  • A multi-target recognition method and system for brachial plexus ultrasound images

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Embodiment Construction

[0053] The specific embodiments of the present invention are described below so that those skilled in the art can understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes Within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are included in the protection list.

[0054] Such as figure 1 As shown, the multi-target recognition method for brachial plexus ultrasound images includes the following steps:

[0055] S1. Unify the size of the ultrasound image of the brachial plexus to be identified as the data to be identified;

[0056] S2. Perform several convolution-downsampling operations on the data to be identified in sequence, and reduce the size of the image obtained by each operation...

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Abstract

The invention discloses a multi-target recognition method and system for brachial plexus ultrasound images. The method includes: acquiring feature maps; acquiring multi-scale feature maps; generating feature maps with different receptive fields; and acquiring features with different scale contrast features Map matrix; obtain the weighted feature map matrix; use each pixel in the weighted feature map matrix as the center point to generate the region of interest, and perform binary classification and detection of the bounding box on the region of interest after regression , align the selected regions into a fixed-size feature map; classify the region of interest in the fixed-size feature map, perform classification, segmentation mask and bounding box detection, and output, and complete the multi-target recognition of the brachial plexus ultrasound image. This method can help anesthesiologists quickly and accurately identify desired multi-target tissues from brachial plexus ultrasound images.

Description

technical field [0001] The invention relates to the field of image recognition, in particular to a multi-target recognition method and system for brachial plexus ultrasound images. Background technique [0002] Brachial plexus block (PNB) is a form of local anesthesia commonly used in surgical procedures. In PNB surgery, the anesthesiologist will first use ultrasound equipment to detect and locate the brachial plexus in ultrasound imaging, and then perform anesthesia for the patient through local anesthesia of the nerve. The branch targets of the brachial plexus and peripheral nerves are small and change dynamically during ultrasound visualization, making identification difficult. Anesthesiologists need to have sufficient knowledge of the structure of the nerve and its surrounding anatomical tissues (muscle tissue, arterial blood vessels, and venous blood vessels) Understand and have rich clinical experience and medical knowledge. Due to the difficulty in identifying nerve...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T7/12G06V10/25G06V10/764G06K9/62
CPCG06T7/0012G06T7/12G06T2207/10132G06T2207/30101G06T2207/20084G06V10/25G06V2201/03G06F18/24
Inventor 丁熠杨祺琪秦志光秦臻张健郑伟张超朱桂钦谭富元
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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