{"title":"Toward a deep augmented reality medical images diagnosis generation","authors":"Sabrine Benzarti, W. Karaa, H. Ghézala","doi":"10.1504/IJIM.2021.10038412","DOIUrl":null,"url":null,"abstract":"Augmented reality (AR) and deep learning (DL) are promising areas. In this paper, we present the impact of such assortment (AR/DL) on the enhancement of generating textual and oral descriptions from a target medical image. The main purpose is to assist medical practitioners to make an accurate decision about a generated diagnosis. Automatic medical image report generation (textual and vocal) is used up as a diagnostic aid system for disease diagnoses depend strongly on visual properties. In this paper, we will describe how we develop an augmented report for the X-ray image target. Primary results using prototypes are promising. Doctors, learner's task are more efficient and feedbacks are encouraging.","PeriodicalId":433219,"journal":{"name":"The International Journal on the Image","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The International Journal on the Image","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJIM.2021.10038412","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Augmented reality (AR) and deep learning (DL) are promising areas. In this paper, we present the impact of such assortment (AR/DL) on the enhancement of generating textual and oral descriptions from a target medical image. The main purpose is to assist medical practitioners to make an accurate decision about a generated diagnosis. Automatic medical image report generation (textual and vocal) is used up as a diagnostic aid system for disease diagnoses depend strongly on visual properties. In this paper, we will describe how we develop an augmented report for the X-ray image target. Primary results using prototypes are promising. Doctors, learner's task are more efficient and feedbacks are encouraging.