{"type":"ScholarlyArticle","title":"Enhancing Boundary Segmentation for Topological Accuracy with Skeleton-based Methods","authors":[{"name":"Chuni Liu","slug":"chuni-liu","given":"Chuni","family":"Liu","affiliation":"Collaborative Innovation Center of Steel Technology , University of Science and Technology Beijing; Beijing Advanced Innovation Center for Materials Genome Engineering , University of Science and Technology Beijing"},{"name":"Boyuan Ma","slug":"boyuan-ma","given":"Boyuan","family":"Ma","affiliation":"Beijing Advanced Innovation Center for Materials Genome Engineering , University of Science and Technology Beijing; School of Intelligence Science and Technology , University of Science and Technology Beijing; Shunde Innovation School , University of Science and Technology Beijing"},{"name":"Xiaojuan Ban","slug":"xiaojuan-ban","given":"Xiaojuan","family":"Ban","affiliation":"Beijing Advanced Innovation Center for Materials Genome Engineering , University of Science and Technology Beijing; School of Intelligence Science and Technology , University of Science and Technology Beijing; Shunde Innovation School , University of Science and Technology Beijing; Institute of Materials Intelligent Technology , Liaoning Academy of Materials"},{"name":"Yujie Xie","slug":"yujie-xie","given":"Yujie","family":"Xie","affiliation":"Beijing Advanced Innovation Center for Materials Genome Engineering , University of Science and Technology Beijing; School of Intelligence Science and Technology , University of Science and Technology Beijing"},{"name":"Hao Wang","slug":"hao-wang","given":"Hao","family":"Wang","affiliation":"Beijing Advanced Innovation Center for Materials Genome Engineering , University of Science and Technology Beijing; Institute for Advanced Materials and Technology , University of Science and Technology Beijing"},{"name":"Weihua Xue","slug":"weihua-xue","given":"Weihua","family":"Xue","affiliation":"School of Materials Science and Technology , Liaoning Technical University"},{"name":"Jingchao Ma","slug":"jingchao-ma","given":"Jingchao","family":"Ma","affiliation":"Collaborative Innovation Center of Steel Technology , University of Science and Technology Beijing"},{"name":"Ke Xu","slug":"ke-xu","given":"Ke","family":"Xu","affiliation":"Collaborative Innovation Center of Steel Technology , University of Science and Technology Beijing"}],"abstract":"Topological consistency plays a crucial role in the task of boundary segmentation for reticular images, such as cell membrane segmentation in neuron electron microscopic images, grain boundary segmentation in material microscopic images and road segmentation in aerial images. In these fields, topological changes in segmentation results have a serious impact on the downstream tasks, which can even exceed the misalignment of the boundary itself. To enhance the topology accuracy in segmentation results, we propose the Skea-Topo Aware loss, which is a novel loss function that takes into account the shape of each object and topological significance of the pixels. It consists of two components. First, a skeleton-aware weighted loss improves the segmentation accuracy by better modeling the object geometry with skeletons. Second, a boundary rectified term effectively identifies and emphasizes topological critical pixels in the prediction errors using both foreground and background skeletons in the ground truth and predictions. Experiments prove that our method improves topological consistency by up to 7 points in VI compared to 13 state-of-art methods, based on objective and subjective assessments across three different boundary segmentation datasets. The code is available at https://github.com/clovermini/Skea_topo.","doi":"10.24963/ijcai.2024/121","url":"https://ijcai.org/proceedings/2024/121","pdf":"https://ijcai.org/proceedings/2024/0121.pdf","markdown":"https://ijcai.org/proceedings/2024/121.md","bibtex":"https://ijcai.org/proceedings/2024/bibtex/121","volume":{"slug":"2024","title":"Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2024","url":"https://ijcai.org/proceedings/2024/","year":2024,"location":"Jeju, Korea","dates":"3-9 August 2024","editors":"Kate Larson","isbn":"978-1-956792-04-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2024"},"section":"Computer Vision","track":"Main Track","number":121,"pages":{"first":1092,"last":1100},"keywords":["Computer Vision: CV: Segmentation","Computer Vision: CV: Biomedical image analysis"],"videos":[],"references":[{"position":1,"raw":"[Arganda-Carreras et al., 2013] Ignacio Arganda-Carreras, H. 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