384 citations · 581 across the 5 of their papers we have counts for
5 papers
BAAF: A benchmark attention adaptive framework for medical ultrasound image segmentation tasks
Gongping Chen, Lei Zhao, Xiaotao Yin +4
The AI-based assisted diagnosis programs have been widely investigated on medical ultrasound images. Complex scenario of ultrasound image, in which the coupled interference of inte…
ESKNet-An enhanced adaptive selection kernel convolution for breast tumors segmentation
Gongping Chen, Lu Zhou, Jianxun Zhang +3
Breast cancer is one of the common cancers that endanger the health of women globally. Accurate target lesion segmentation is essential for early clinical intervention and postoper…
Rethinking the Unpretentious U-net for Medical Ultrasound Image Segmentation
Gongping Chen, Lei Li, JianXun Zhang +1
Breast tumor segmentation is one of the key steps that helps us characterize and localize tumor regions. However, variable tumor morphology, blurred boundary, and similar intensity…
BAGNet: Bidirectional Aware Guidance Network for Malignant Breast lesions Segmentation
Gongping Chen, Yuming Liu, Yu Dai +3
Breast lesions segmentation is an important step of computer-aided diagnosis system, and it has attracted much attention. However, accurate segmentation of malignant breast lesions…
AAU-net: An Adaptive Attention U-net for Breast Lesions Segmentation in Ultrasound Images
Gongping Chen, Yu Dai, Jianxun Zhang +1
Various deep learning methods have been proposed to segment breast lesion from ultrasound images. However, similar intensity distributions, variable tumor morphology and blurred bo…