{"title":"Automatic 3D Point Set Reconstruction from Stereo Laparoscopic Images using Deep Neural Networks","authors":"B. Antal","doi":"10.5220/0006008001160121","DOIUrl":null,"url":null,"abstract":"In this paper, an automatic approach to predict 3D coordinates from stereo laparoscopic images is presented. The approach maps a vector of pixel intensities to 3D coordinates through training a six layer deep neural network. The architectural aspects of the approach is presented and in detail and the method is evaluated on a publicly available dataset with promising results.","PeriodicalId":298357,"journal":{"name":"International Conference on Pervasive and Embedded Computing and Communication Systems","volume":"39 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Pervasive and Embedded Computing and Communication Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0006008001160121","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this paper, an automatic approach to predict 3D coordinates from stereo laparoscopic images is presented. The approach maps a vector of pixel intensities to 3D coordinates through training a six layer deep neural network. The architectural aspects of the approach is presented and in detail and the method is evaluated on a publicly available dataset with promising results.