6 citations · 6 across the 3 of their papers we have counts for
4 papers
EMT-NET: Efficient multitask network for computer-aided diagnosis of breast cancer
Jiaqiao Shi, Aleksandar Vakanski, Min Xian +2
Deep learning-based computer-aided diagnosis has achieved unprecedented performance in breast cancer detection. However, most approaches are computationally intensive, which impede…
Breast Anatomy Enriched Tumor Saliency Estimation
Fei Xu, Yingtao Zhang, Min Xian +5
Breast cancer investigation is of great significance, and developing tumor detection methodologies is a critical need. However, it is a challenging task for breast ultrasound due t…
Tumor Saliency Estimation for Breast Ultrasound Images via Breast Anatomy Modeling
Fei Xu, Yingtao Zhang, Min Xian +5
Tumor saliency estimation aims to localize tumors by modeling the visual stimuli in medical images. However, it is a challenging task for breast ultrasound due to the complicated a…
A Hybrid Framework for Tumor Saliency Estimation
Fei Xu, Min Xian, Yingtao Zhang +6
Automatic tumor segmentation of breast ultrasound (BUS) image is quite challenging due to the complicated anatomic structure of breast and poor image quality. Most tumor segmentati…