Improved breast ultrasound tumor classification using dual-input CNN with GAP-guided attention loss

Improved breast ultrasound tumor classification using dual-input CNN with GAP-guided attention loss

Ultrasonography is a widely used medical imaging technique for detecting breast cancer. While manual diagnostic methods are subject to variability and time-consuming, computer-aided diagnostic (CAD) methods have proven to be more efficient. However, current CAD approaches neglect the impact of noise...

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Bibliographic Details
Main Authors: Xiao Zou, Jintao Zhai, Shengyou Qian, Ang Li, Feng Tian, Xiaofei Cao, Runmin Wang
Format: Article
Language:English
Published: AIMS Press 2023-07-01
Series:Mathematical Biosciences and Engineering
Subjects:
ultrasound image
breast ultrasound tumor
convolutional neural network
feature fusion
classification
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2023682?viewType=HTML

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https://www.aimspress.com/article/doi/10.3934/mbe.2023682?viewType=HTML

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