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Found 6 papers, 4 papers with code
PSFHS Challenge Report: Pubic Symphysis and Fetal Head Segmentation from Intrapartum Ultrasound Images
This challenge aimed to enhance the development of automatic segmentation algorithms at an international scale, providing the largest dataset to date with 5, 101 intrapartum ultrasound images collected from two ultrasound machines across three hospitals from two institutions.
A simple thinking about the application of the attention mechanism in medical ultrasound image segmentation task
The AI-based assisted diagnosis programs have been widely investigated on medical ultrasound images.
ESKNet-An enhanced adaptive selection kernel convolution for breast tumors segmentation
Breast cancer is one of the common cancers that endanger the health of women globally.
Rethinking the Unpretentious U-net for Medical Ultrasound Image Segmentation
However, variable tumor morphology, blurred boundary, and similar intensity distributions bring challenges for accurate segmentation of breast tumors.
BAGNet: Bidirectional Aware Guidance Network for Malignant Breast lesions Segmentation
Breast lesions segmentation is an important step of computer-aided diagnosis system, and it has attracted much attention.
AAU-net: An Adaptive Attention U-net for Breast Lesions Segmentation in Ultrasound Images
Different from existing attention mechanisms, the hybrid adaptive attention module can guide the network to adaptively select more robust representation in channel and space dimensions to cope with more complex breast lesions segmentation.
