A 3D visualization‐based augmented reality application for brain tumor segmentation

Author:

Guerroudji Mohamed Amine1ORCID,Amara Kahina1,Lichouri Mohamed2,Zenati Nadia1,Masmoudi Mostefa1

Affiliation:

1. Division of Robotics and Industrial Automation Center for Development of Advanced Technologies (CDTA) Baba Hassen Algeria

2. Department of Telecommunications University of science and technology Houari Boumediene (USTHB) Algiers Algeria

Abstract

SummaryEvery year on June 8th, the globe observes World Brain Tumor Day to raise awareness and educate people about brain cancer, encompassing both noncancerous (benign) and cancerous (malignant) growths. Research in the field of brain cancer plays a vital role in supporting medical professionals. In this context, augmented reality (AR) technology has emerged as a valuable tool, enabling surgeons to visualize underlying structures and offering a cost‐effective and time‐efficient alternative. Our study focuses on the efficient segmentation of brain tumor classes using Magnetic Resonance Imaging (MRI) and incorporates a three‐stage approach: preprocessing, segmentation, and 3D reconstruction & AR display. In the preprocessing stage, a Gaussian filter is applied to mitigate intensity heterogeneity. Segmentation and detection are achieved using active geometric contour models, complemented by morphological operations. To establish 3D brain tumor reconstruction, a genuine scene is virtually integrated using 3D Slicer software. The proposed methodology was validated using a genuine patient dataset comprising 496 MRI scans obtained from the local Bab El Oued university hospital center. The results demonstrate the effectiveness of our approach in achieving accurate 3D brain tumor reconstruction, efficient tumor extraction, and augmented reality visualization. The obtained segmentation results showcased an impressive accuracy of 98.61%, outperforming existing state‐of‐the‐art methods and affirming the efficacy of our proposed strategy.

Publisher

Wiley

Subject

Computer Graphics and Computer-Aided Design,Software

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Automatic Surgery in Transcatheter Aortic Valve Replacement Using Augmented Reality;Journal of Visualized Experiments;2024-08-09

2. Augmented Reality localisation using 6 DoF phantom head Pose Estimation-based generalisable Deep Learning model;2024 8th International Conference on Image and Signal Processing and their Applications (ISPA);2024-04-21

3. Advancing Brain Tumor Detection: A Cutting-Edge Machine Learning Approach Leveraging CAD Systems;2024 8th International Conference on Image and Signal Processing and their Applications (ISPA);2024-04-21

4. HoloBrain: 3D low-cost mobile augmented reality rendering of brain tumour using the GVF snake model segmentation;Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization;2024-01-13

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