|Table of Contents|

Features Guidance Axillary Lymph Nodes Network for Breast Cancer Segmentation(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2023年02期
Page:
92-98
Research Field:
计算机科学与技术
Publishing date:

Info

Title:
Features Guidance Axillary Lymph Nodes Network for Breast Cancer Segmentation
Author(s):
Ban Kaidi1; 2; 3; Sun Yu2; 3; Han Yue2; 3; Wei Benzheng2; 3
(1.College of Innovative Institute of Chinese Medicine and Pharmacy,Shandong University of Traditional Chinese Medicine,Jinan 250355,China)
(2.Center for Medical Artificial Intelligence,Shandong University of Traditional Chinese Medicine,Qingdao 266112,China)
(3.Qingdao Academy of Chinese Medical Sciences,Shandong University of Traditional Chinese Medicine,Qingdao 266112,China)
Keywords:
Axillary lymph nodes;  image segmentation;  deep learning;  ultrasonic images;  segmentation network
PACS:
TP391
DOI:
10.3969/j.issn.1001-4616.2023.02.012
Abstract:
Ultrasound image segmentation of axillary lymph nodes is a clinically valuable and challenging task, which is of great significance for the diagnosis of breast cancer. In order to improve the clinical segmentation accuracy of axillary lymph nodes, Aiming at the characteristics of axillary lymph nodes ultrasonic images, on the encoder decoder architecture, this paper designs a feature guidance module to achieve efficient feature fusion and coefficient exploration in feature extraction, and on this basis, the features guidance network of axillary lymph nodes is proposed to achieve accurate identification and segmentation of axillary lymph nodes in ultrasound images. Experiments show that on the dataset of 712 axillary lymph node ultrasound images, the m-ACC of this algorithm is 0.977, the m-IoU score is 0.878, and the m-Dice can reach 0.932, which is better than the existing segmentation model, and the segmentation results can be used as a clinical diagnosis reference to assist in the accurate diagnosis of axillary lymph node metastasis in breast cancer.

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Last Update: 2023-06-15