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MSRF-Net: A Multi-Scale Residual Fusion Network for Biomedical Image Segmentation
2021
IEEE journal of biomedical and health informatics
Methods based on convolutional neural networks have improved the performance of biomedical image segmentation. However, most of these methods cannot efficiently segment objects of variable sizes and train on small and biased datasets, which are common for biomedical use cases. While methods exist that incorporate multi-scale fusion approaches to address the challenges arising with variable sizes, they usually use complex models that are more suitable for general semantic segmentation problems.
doi:10.1109/jbhi.2021.3138024
pmid:34941539
fatcat:nup65lzcl5dlflvgzv4tf7uosi