{"title":"利用器官特异性深度学习将牙科锥束计算机断层扫描中的剂量-面积乘积转换为有效剂量","authors":"Ruben Pauwels","doi":"10.1101/2024.05.28.24308014","DOIUrl":null,"url":null,"abstract":"<strong>Objective</strong> To develop an accurate method for converting dose-area product (DAP) to patient dose for dental cone-beam computed tomography (CBCT) using deep learning.","PeriodicalId":501363,"journal":{"name":"medRxiv - Dentistry and Oral Medicine","volume":"26 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Converting dose-area product to effective dose in dental cone-beam computed tomography using organ-specific deep learning\",\"authors\":\"Ruben Pauwels\",\"doi\":\"10.1101/2024.05.28.24308014\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<strong>Objective</strong> To develop an accurate method for converting dose-area product (DAP) to patient dose for dental cone-beam computed tomography (CBCT) using deep learning.\",\"PeriodicalId\":501363,\"journal\":{\"name\":\"medRxiv - Dentistry and Oral Medicine\",\"volume\":\"26 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"medRxiv - Dentistry and Oral Medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2024.05.28.24308014\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Dentistry and Oral Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.05.28.24308014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Converting dose-area product to effective dose in dental cone-beam computed tomography using organ-specific deep learning
Objective To develop an accurate method for converting dose-area product (DAP) to patient dose for dental cone-beam computed tomography (CBCT) using deep learning.
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