{"type":"ScholarlyArticle","title":"IPSM-Bench: A New Intermediate Phase Segmentation Benchmark in Microstructure Images of Zinc-Based Absorbable Biomaterials","authors":[{"name":"Jinglin Xu","slug":"jinglin-xu","given":"Jinglin","family":"Xu","affiliation":""},{"name":"Shangyan Zhao","slug":"shangyan-zhao","given":"Shangyan","family":"Zhao","affiliation":""},{"name":"Jiabo Wang","slug":"jiabo-wang","given":"Jiabo","family":"Wang","affiliation":""},{"name":"Xinghong Mu","slug":"xinghong-mu","given":"Xinghong","family":"Mu","affiliation":""},{"name":"Yulong Lei","slug":"yulong-lei","given":"Yulong","family":"Lei","affiliation":""},{"name":"Jiacheng Zhang","slug":"jiacheng-zhang","given":"Jiacheng","family":"Zhang","affiliation":""},{"name":"Hongbo Sun","slug":"hongbo-sun","given":"Hongbo","family":"Sun","affiliation":""},{"name":"Yageng Li","slug":"yageng-li","given":"Yageng","family":"Li","affiliation":""}],"abstract":"Zinc-based alloys are indispensable emerging absorbable metallic biomaterials, and their macroscopic performance is governed by microstructural characteristics. Intermediate phases—key microstructural constituents—are pivotal in regulating mechanical and functional properties. However, intermediate phase segmentation in zinc alloy microstructures faces formidable challenges: scarce annotated datasets, low contrast, difficulty detecting small targets, and heterogeneous morphologies. To this end, we construct IPSM-Bench, the largest high-quality dataset for zinc-alloy intermediate phase segmentation. Furthermore, we propose SCoP-SAM, a new Spatial Context Prior-guided SAM method that leverages the gradient structure and grayscale properties of intermediate phases to capture spatial context priors and incorporates them into the entire SAM encoding-decoding process, improving segmentation performance. Based on the proposed IPSM-Bench, we establish a new benchmark for intermediate phase segmentation to systematically evaluate state-of-the-art (SOTA) methods and advance research on zinc alloy microstructure analysis. Extensive experiments on IPSM-Bench and additional public alloy benchmarks demonstrate that our SCoP-SAM not only achieves SOTA performance for zinc-alloy intermediate phase segmentation but also generalizes remarkably well to other alloy scenarios.","doi":"10.24963/ijcai.2026/215","url":"https://ijcai.org/proceedings/2026/215","pdf":"https://ijcai.org/proceedings/2026/0215.pdf","markdown":"https://ijcai.org/proceedings/2026/215.md","bibtex":"https://ijcai.org/proceedings/2026/bibtex/215","volume":{"slug":"2026","title":"Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2026","url":"https://ijcai.org/proceedings/2026/","year":2026,"location":"Bremen, Germany","dates":"15-21 August 2026","editors":"Diego Calvanese","isbn":"978-1-956792-09-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2026"},"section":"Computer Vision","track":"Main Track","number":215,"pages":{"first":1929,"last":1937},"keywords":["Computer Vision: Segmentation, grouping and shape analysis","Multidisciplinary Topics and Applications: Other"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}