Abstract:Due to the blurry edges and uneven shape of breast tumors, breast
tumor segmentation can be a challenging task. Recently, deep convolution networks
(DCNs) based approaches achieve satisfying segmentation results. However, the
learned shape information of breast tumors might be lost owing to the successive
convolution and down-sampling operations, resulting in limited performance. To this
end, we propose a novel Shape-Guided Segmentation (SGS) framework that guides&#x… Show more
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