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Found 5 papers, 3 papers with code
A Complementary Global and Local Knowledge Network for Ultrasound denoising with Fine-grained Refinement
However, the presence of speckle noise in ultrasound images invariably degrades image quality, impeding the performance of subsequent tasks, such as segmentation and classification.
CANet: Channel Extending and Axial Attention Catching Network for Multi-structure Kidney Segmentation
In this paper, we propose a channel extending and axial attention catching Network(CANet) for multi-structure kidney segmentation.
FFCNet: Fourier Transform-Based Frequency Learning and Complex Convolutional Network for Colon Disease Classification
Reliable automatic classification of colonoscopy images is of great significance in assessing the stage of colonic lesions and formulating appropriate treatment plans.
AWSnet: An Auto-weighted Supervision Attention Network for Myocardial Scar and Edema Segmentation in Multi-sequence Cardiac Magnetic Resonance Images
Extensive experimental results on a publicly available dataset from Myocardial pathology segmentation combining multi-sequence CMR (MyoPS 2020) demonstrate our method can achieve promising performance compared with other state-of-the-art methods.
Learn Fine-grained Adaptive Loss for Multiple Anatomical Landmark Detection in Medical Images
Our proposed framework is general and shows the potential to improve the efficiency of anatomical landmark detection.
