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Found 4 papers, 1 papers with code
Breast Ultrasound Tumor Classification Using a Hybrid Multitask CNN-Transformer Network
Vision Transformers have an improved capability of capturing global contextual information but may distort the local image patterns due to the tokenization operations.
SIAN: Style-Guided Instance-Adaptive Normalization for Multi-Organ Histopathology Image Synthesis
Existing deep neural networks for histopathology image synthesis cannot generate image styles that align with different organs, and cannot produce accurate boundaries of clustered nuclei.
ESTAN: Enhanced Small Tumor-Aware Network for Breast Ultrasound Image Segmentation
Breast tumor segmentation is a critical task in computer-aided diagnosis (CAD) systems for breast cancer detection because accurate tumor size, shape and location are important for further tumor quantification and classification.
Stan: Small tumor-aware network for breast ultrasound image segmentation
The proposed approach outperformed the state-of-the-art approaches in segmenting small breast tumors.
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