{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T12:27:03Z","timestamp":1775651223324,"version":"3.50.1"},"reference-count":34,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T00:00:00Z","timestamp":1775606400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"NOAA\u2019s Ruth Gates Coral Restoration Innovation Grant","award":["NA22NMF4820207"],"award-info":[{"award-number":["NA22NMF4820207"]}]},{"name":"Florida Department of Environmental Protection\u2019s Coral Protection and Restoration Program","award":["CPRP_C5B5BD"],"award-info":[{"award-number":["CPRP_C5B5BD"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Coral reef ecosystems are declining rapidly due to climate change, disease, and anthropogenic stressors, driving the expansion of land-based coral propagation for reef restoration. A major bottleneck in these efforts is the manual measurement of coral recruit tissue area from microscopy images, which requires 2\u20137 min per image and limits scalability. We present a hierarchical deep learning pipeline that automates this measurement by integrating YOLO-based detection with Segment Anything Model (SAM) segmentation. YOLO localizes recruits and classifies them by developmental stage; stage-specific fine-tuned SAM models then segment live tissue using bounding box and background point prompts to suppress segmentation leakage and improve boundary precision. Surface area is computed directly from the segmented masks using pixel size extracted from image metadata. The pipeline reduces processing time to approximately 3\u20135 s per image\u2014a 24\u2013140\u00d7 speedup over manual tracing. Evaluated on 3668 microscopy images from two national coral research facilities, the system achieves a mean IoU exceeding 95% and an auto-acceptance rate (AAR) of 71.51%, where predicted-to-ground-truth area ratios fall within a \u00b15% tolerance of expert annotation, substantially reducing manual workload while maintaining measurement reliability across species, developmental stages, and imaging conditions. This workflow addresses a critical bottleneck in restoration research and demonstrates the broader applicability of AI-based image analysis in marine ecology.<\/jats:p>","DOI":"10.3390\/s26082291","type":"journal-article","created":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T11:41:18Z","timestamp":1775648478000},"page":"2291","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Hierarchical YOLO-SAM: A Scalable Pipeline for Automated Segmentation and Morphometric Tracking of Coral Recruits in Time-Series Microscopy"],"prefix":"10.3390","volume":"26","author":[{"given":"Richard S.","family":"Zhao","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0938-8841","authenticated-orcid":false,"given":"Cuixian","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, University of North Carolina Wilmington, Wilmington, NC 28403, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6666-4472","authenticated-orcid":false,"given":"Meg","family":"Van Horn","sequence":"additional","affiliation":[{"name":"Department of Biology and Marine Biology, Center for Marine Science, University of North Carolina Wilmington, Wilmington, NC 28403, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicole D.","family":"Fogarty","sequence":"additional","affiliation":[{"name":"Department of Biology and Marine Biology, Center for Marine Science, University of North Carolina Wilmington, Wilmington, NC 28403, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1278","DOI":"10.1016\/j.oneear.2021.08.016","article-title":"Global decline in capacity of coral reefs to provide ecosystem services","volume":"4","author":"Eddy","year":"2021","journal-title":"One Earth"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1016\/S0921-8009(99)00009-9","article-title":"Ecological goods and services of coral reef ecosystems","volume":"29","author":"Moberg","year":"1999","journal-title":"Ecol. 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