Cervical biopsy region recognition method and device based on channel information multimodal network

Abstract

The invention discloses a method and a device for identifying a cervical biopsy area based on a multimodal network of channel information. The device includes: an image acquisition unit, which collects physiological saline images, acetic acid images and iodine images of the cervix; and a data processing unit, which includes trained The cervical biopsy area recognition model analyzes and processes the normal saline image, acetic acid image and iodine image, and outputs the probability label of the cervical biopsy area; the cervical biopsy area recognition model includes: the detection network layer, which is used to extract the normal saline image, acetic acid image and The feature map and location information of the cervical surface area in the iodine image; the feature combination prediction network layer splices the three feature maps and location information in the channel dimension, and then outputs the probability label of the biopsy area of ​​the cervix through feature fusion and identification; Display unit, get probability label and display. The cervical biopsy area identification device can assist the doctor to make an accurate judgment on whether further biopsy of the patient's cervix is ​​required.

Description

technical field [0001] The invention relates to the field of medical image processing, in particular to a method and device for identifying cervical biopsy regions based on channel information multimodal networks. Background technique [0002] Cervical cancer is the most common gynecological malignancy. The high-incidence age of carcinoma in situ is 30-35 years old, and that of invasive carcinoma is 45-55 years old. In recent years, the onset tends to be younger. [0003] The inspection steps of cervical lesions are mainly divided into three steps: (1) cervical cytology examination, the most commonly used is the Pap smear method; (2) colposcopy, if the cytology results are abnormal, colposcopy examination is required, observation Changes in cervical epithelial color, blood vessels, etc.; (3) Cervical tissue biopsy. If there is any doubt in colposcopy, the doctor will take a small amount of cervical tissue from the suspicious lesion for biopsy under the positioning of the co...

AI Technical Summary

Problems solved by technology

At present, many machine learning and deep learning methods have been applied to colposcopy detection images, including the detection of cervical os, the detection of acetabular areas, and the prediction of the degree of cervical lesions. Although these methods can play a certain role in assisting function, but cannot assist doctors to make more accurate judgments from the root cause

Moreover, most of these methods only use colposcopic cervical images with 3%-5% acetic acid solution, which is combined with the characteristic changes of doctors through 0.9% normal saline, 3%-5% acetic acid solution, compound iodine solution and other images to determine whether there is cervical cancer. Inconsistent medical procedures in the area of ​​the biopsy

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