DA-RefineNet:A Dual Input Whole Slide Image Segmentation Algorithm Based on Attention
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Due to the high resolution of pathological images, the automated semantic segmentation in the medical pathological images has shown greater challenges than that in natural images. Sliding Window method has shown its effect on solving problem caused by the high resolution of whole slide images (WSI). However, owing to its localization, Sliding Window method also suffers from lack of global information. In this paper, a dual input semantic segmentation network based on attention is proposed, in which, one input provides small-scale fine information, the other input provides large-scale coarse information. Compared with single input methods, our method based on dual inputs and attention: DA-RefineNet exhibits a dramatic performance improvement on ICIAR2018 breast cancer segmentation task.
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