{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,3]],"date-time":"2025-10-03T13:04:29Z","timestamp":1759496669858,"version":"3.37.3"},"reference-count":15,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,4,13]],"date-time":"2021-04-13T00:00:00Z","timestamp":1618272000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,4,13]],"date-time":"2021-04-13T00:00:00Z","timestamp":1618272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,4,13]],"date-time":"2021-04-13T00:00:00Z","timestamp":1618272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100006420","name":"Bucknell University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006420","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,4,13]]},"DOI":"10.1109\/isbi48211.2021.9433868","type":"proceedings-article","created":{"date-parts":[[2021,5,25]],"date-time":"2021-05-25T20:14:15Z","timestamp":1621973655000},"page":"1007-1011","source":"Crossref","is-referenced-by-count":5,"title":["Bayesian Optimization of 2D Echocardiography Segmentation"],"prefix":"10.1109","author":[{"given":"Tung","family":"Tran","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joshua V.","family":"Stough","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christopher M.","family":"Haggerty","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","article-title":"Botorch: Programmable bayesian optimization in pytorch","author":"balandat","year":"2019","journal-title":"arXiv preprint arXiv 1910 01500"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1214\/18-BA1110","article-title":"Constrained bayesian optimization with noisy experiments","volume":"14","author":"letham","year":"2019","journal-title":"Bayesian Analysis"},{"journal-title":"Camus Cardiac acquisitions for multi-structure ultrasound segmentation","year":"0","author":"leclerc","key":"ref12"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1111\/echo.12331"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-020-2145-8"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1959.10501526"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2900516"},{"key":"ref3","first-page":"234","author":"ronneberger","year":"2015","journal-title":"U-net Convolutional networks for biomedical image segmentation"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1117\/12.2547375"},{"key":"ref5","article-title":"Temporal-consistent segmentation of echocardiography with colearning from appearance and shape","author":"wei","year":"2020","journal-title":"MICCAI"},{"key":"ref8","first-page":"2951","article-title":"Practical bayesian optimization of machine learning algorithms","author":"snoek","year":"2012","journal-title":"Advances in neural information processing systems"},{"key":"ref7","article-title":"Convergence rates of efficient global optimization algorithms","volume":"12","author":"bull","year":"2011","journal-title":"Journal of Machine Learning Research"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCULATIONAHA.118.034338"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1093\/ehjci\/jev014"},{"key":"ref9","article-title":"A tutorial on bayesian optimization","author":"frazier","year":"2018","journal-title":"ArXiv"}],"event":{"name":"2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)","start":{"date-parts":[[2021,4,13]]},"location":"Nice, France","end":{"date-parts":[[2021,4,16]]}},"container-title":["2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9433749\/9433753\/09433868.pdf?arnumber=9433868","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T15:41:52Z","timestamp":1652197312000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9433868\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,13]]},"references-count":15,"URL":"https:\/\/doi.org\/10.1109\/isbi48211.2021.9433868","relation":{},"subject":[],"published":{"date-parts":[[2021,4,13]]}}}