Ultrasonic breast tumor automatic segmentation method based on attention-enhanced U-shaped network

A technology for automatic segmentation of breast tumors, applied in the field of ultrasound breast tumor detection, can solve the problems of low contrast of ultrasound images, further improvement of segmentation effect, lack of training data, etc.

Inactive Publication Date: 2021-02-09
南京天智信科技有限公司
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Problems solved by technology

However, due to the lack of training data, the low contrast of ultrasound images, the mutual invasion between suspicious lesions and surrounding tissues, and the diversity of tumor s

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  • Ultrasonic breast tumor automatic segmentation method based on attention-enhanced U-shaped network
  • Ultrasonic breast tumor automatic segmentation method based on attention-enhanced U-shaped network
  • Ultrasonic breast tumor automatic segmentation method based on attention-enhanced U-shaped network

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Embodiment Construction

[0053]The present invention will be further described below in conjunction with the accompanying drawings of the specification.

[0054]Such asfigure 1 As shown, the automatic segmentation method of ultrasonic breast tumor based on Attention-enhancing Unet (AE-Unet) of the present invention includes the following steps:

[0055]Step (A), construct an attention-enhanced U-shaped network model for automatic segmentation of ultrasound breast tumors such asfigure 2 andimage 3 As shown, including the following steps,

[0056](A1) Establish a left-side contraction path. The left-side contraction path includes three arithmetic modules of left convolution, downsampling, and left modified linear unit (Relu). The left convolution arithmetic module is used to extract the deep semantic features of the image. The size of the convolution kernel of all left convolution budget modules is 3*3; after each left convolution operation, the activation function of the left Relu operation module is required to enha...

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Abstract

The invention discloses an ultrasonic breast tumor automatic segmentation method based on an attention-enhanced U-shaped network. The method comprises the following steps: (A) constructing an attention-enhanced U-shaped network model for ultrasonic breast tumor automatic segmentation; step (B), establishing a mixed attention loss function of the attention enhancement U-shaped network model; and step (C), according to the attention-enhanced U-shaped network model and the mixed attention loss function, training the attention-enhanced U-shaped network model through a coarse and fine combination strategy to achieve segmentation of the breast ultrasound image lesion area. The method can be used for extracting the focus area of the mammary gland ultrasonic image, can effectively improve the accuracy of mammary gland tumor segmentation, is used for assisting a doctor in quickly and accurately positioning the focus area, reducing the workload of the doctor and relieving the defects of insufficient clinical experience and the like of young doctors, and has very important research value and application prospect for modern medicine.

Description

Technical field[0001]The present invention relates to the technical field of ultrasonic breast tumor detection, in particular to a method for automatically segmenting ultrasonic breast tumors based on an attention-enhanced U-shaped network.Background technique[0002]At present, breast cancer is a disease that seriously endangers women's health after skin cancer. With the development of modern medicine, early diagnosis and treatment can greatly improve the survival rate of breast cancer patients. Currently, the diagnosis of breast tumors can be divided into invasive and non-invasive diagnosis. Invasive diagnosis mainly refers to biopsy, but this will cause physical damage to breast tissue and cause pain to the patient; non-invasive diagnosis refers to the use of X-ray, MRI (magnetic resonance imaging) or ultrasound imaging to examine breast lesions Among various inspection methods, ultrasound imaging has become the first choice for early diagnosis of breast tumors due to the advantage...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/11G06N3/04G06N3/08G06T5/40
CPCG06T7/0012G06T7/11G06T5/40G06N3/08G06T2207/10132G06T2207/30068G06T2207/30096G06T2207/20081G06T2207/20084G06N3/048G06N3/045
Inventor 童莹赵曼雪
Owner 南京天智信科技有限公司
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