{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,31]],"date-time":"2024-08-31T05:47:26Z","timestamp":1725083246644},"reference-count":0,"publisher":"IOS Press","license":[{"start":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T00:00:00Z","timestamp":1653436800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,25]]},"abstract":"<jats:p>In this work, we propose a method to segment endoscope and guidewire from 2D X-ray fluoroscopic images of an endoscopic retrograde cholangiopancreatography (ERCP). We used an improved U-Net model. We obtained a Dice score of 0.94\u00b10.05 for endoscope segmentation and a Hausdorff distance of 24.26 pixels for the guidewire segmentation. These preliminary results pave the way for further applications aiming at aiding the medical procedure.<\/jats:p>","DOI":"10.3233\/shti220416","type":"book-chapter","created":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T12:13:00Z","timestamp":1653480780000},"source":"Crossref","is-referenced-by-count":1,"title":["Instruments Segmentation in X-ray Fluoroscopic Images for Endoscopic Retrograde Cholangio Pancreatography"],"prefix":"10.3233","author":[{"given":"Garance","family":"Martin","sequence":"first","affiliation":[{"name":"Sorbonne Universit\u00e9, CNRS, LIP6, Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Saad","family":"El-Madafri","sequence":"additional","affiliation":[{"name":"Sorbonne Universit\u00e9, CNRS, LIP6, Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aymeric","family":"Becq","sequence":"additional","affiliation":[{"name":"Sorbonne Universit\u00e9, CNRS, INSERM, ISIR, Paris, France"},{"name":"UPEC, H\u00f4pital Henri Mondor, Service de Gastroent\u00e9rologie, APHP, Cr\u00e9teil, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J\u00e9r\u00f4me","family":"Szewczyk","sequence":"additional","affiliation":[{"name":"Sorbonne Universit\u00e9, CNRS, INSERM, ISIR, Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Isabelle","family":"Bloch","sequence":"additional","affiliation":[{"name":"Sorbonne Universit\u00e9, CNRS, LIP6, Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Challenges of Trustable AI and Added-Value on Health"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI220416","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T12:13:00Z","timestamp":1653480780000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI220416"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,25]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti220416","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,25]]}}}