D-TransUNet: A Breast Tumor Ultrasound Image Segmentation Model Based on Deep Feature Fusion

Research Articie March 18,2024

Yiying Wan ¹ , Yaru Yang ² , Hongjiang Guo ³ , Yangtian Yan ⁴ , Tongtong Liu ⁵ , Wenpei Liu ⁶ , Yiru Wang ⁷ , Wenhang Wang ⁸ , Hao Dang ⁹ hide author's information

1 : School of Information Technology, Henan University of Chinese Medicine, Zhengzhou 450046
2 : School of Information Technology, Henan University of Chinese Medicine, Zhengzhou 450046
3 : School of Information Technology, Henan University of Chinese Medicine, Zhengzhou 450046
4 : School of Information Technology, Henan University of Chinese Medicine, Zhengzhou 450046
5 : School of Information Technology, Henan University of Chinese Medicine, Zhengzhou 450046
6 : School of Information Technology, Henan University of Chinese Medicine, Zhengzhou 450046
7 : School of Information Technology, Henan University of Chinese Medicine, Zhengzhou 450046
8 : School of Information Technology, Henan University of Chinese Medicine, Zhengzhou 450046
9 : School of Information Technology, Henan University of Chinese Medicine; Zhengzhou Key Laboratory of Intelligent Analysis and Utilization of Traditional Chinese Medicine Information, Zhengzhou

DOI: 10.55578/joaims.240226.001

Keywords: Breast tumor ultrasound image segmentation; Central dense connection; TransUNet; Deep learning

Cite this article: Wan, Yiying et al., D-TransUNet: A Breast Tumor Ultrasound Image Segmentation Model Based on Deep Feature Fusion, JOAIMS (2024), 1-8, In Press.

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Abstract

Breast ultrasound is a widely utilized modality for breast cancer screening since its noninvasive,

radiation-free, low-cost, and easy-to-operate characteristics...