Towards a deep augmented reality medical images diagnosis generation. (16th June 2021)

• Record Type: Journal Article
• Authors: Benzarti, Sabrine; Karaa, Wahiba Ben Abdessalem; Ghezala, Henda Hajjami Ben
• Is Part Of: International journal of image mining. Volume 4:Number 1(2020)
• Page Start: 59
• Page End: 68
• Publication Date: 2021-06-16
• Subjects: CNN -- RNN -- image captioning -- augmented reality -- medical image diagnosis generation; Image processing -- Periodicals; Data mining -- Periodicals; 006.42
• Languages: English
• ISSNs: 2055-6039

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.