Multimodal fusion of ultrasound images using HXM net for breast cancer diagnosis.

ABSTRACT: Breast cancer is a major global health issue in women, where diagnosis at an early stage is decisive for enhancing the effectiveness of treatment and survival. Despite the advances in imaging using medical technologies, maintaining uniformly good diagnostic accuracy is challenging due to the difficulty of lesion characterization and limitations of single-modality imaging. This work presents HXM-Net, a deep learning model specifically tailored to improve breast cancer detection through the synergistic benefit of multi-modal ultrasound imaging. HXM-Net combines Convolutional Neural Networks (CNNs) for spatial feature extraction and Transformer-based fusion for optimal concatenation of information from the B-mode and Doppler ultrasound images. The dual modality-based method captures morpholog

SUBMITTER: Ghantasala GSP 

PROVIDER: S-EPMC12630858 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature