{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/focusnet-an-attention-based-fully","title":"FocusNet: An attention-based Fully Convolutional Network for Medical Image Segmentation","arxiv_id":"1902.03091","date":"2019-02-08","proceeding":null,"authors":["Chaitanya Kaul","Suresh Manandhar","Nick Pears"],"abstract":"We propose a novel technique to incorporate attention within convolutional\nneural networks using feature maps generated by a separate convolutional\nautoencoder. Our attention architecture is well suited for incorporation with\ndeep convolutional networks. We evaluate our model on benchmark segmentation\ndatasets in skin cancer segmentation and lung lesion segmentation. Results show\nhighly competitive performance when compared with U-Net and it's residual\nvariant.","url_abs":"http://arxiv.org/abs/1902.03091v1","url_pdf":"http://arxiv.org/pdf/1902.03091v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"focusnet-an-attention-based-fully","repo_url":"https://github.com/MaczekO/AttentionNetworkProject","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"image-segmentation","task_name":"Image Segmentation"},{"task_slug":"lesion-segmentation","task_name":"Lesion Segmentation"},{"task_slug":"medical-image-segmentation","task_name":"Medical Image Segmentation"},{"task_slug":"segmentation","task_name":"Segmentation"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"},{"task_slug":"skin-cancer-segmentation","task_name":"Skin Cancer Segmentation"}],"methods":[{"method_slug":"concatenated-skip-connection","method_name":"Concatenated Skip Connection"},{"method_slug":"convolution","method_name":"Convolution"},{"method_slug":"max-pooling","method_name":"Max Pooling"},{"method_slug":"relu","method_name":"ReLU"},{"method_slug":"u-net","method_name":"U-Net"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}