Toward a deep augmented reality medical images diagnosis generation

Sabrine Benzarti, W. Karaa, H. Ghézala
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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.
面向深度增强现实医学图像诊断生成
增强现实(AR)和深度学习(DL)是有前景的领域。在本文中,我们提出了这种分类(AR/DL)对增强从目标医学图像生成文本和口头描述的影响。其主要目的是帮助医生对生成的诊断做出准确的决定。医学图像自动生成(文本和语音)是一种非常依赖视觉特性的疾病诊断辅助系统。在本文中,我们将描述如何为x射线图像目标开发增强报告。使用原型的初步结果是有希望的。医生,学习者的任务更有效率,反馈是令人鼓舞的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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