HELICoiD: interdisciplinary and collaborative project for real-time brain cancer detection: Invited Paper

R. Salvador, S. Ortega, D. Madroñal, H. Fabelo, R. Lazcano, G. Callicó, E. Juárez, R. Sarmiento, C. Sanz
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引用次数: 7

Abstract

The HELICoiD project is a European FP7 FET Open funded project. It is an interdisciplinary work at the edge of the biomedical domain, bringing together neurosurgeons, computer scientists and electronic engineers. The main target of the project was to provide a working demonstrator of an intraoperative image-guided surgery system for real-time brain cancer detection, in order to assist neurosurgeons during tumour resection procedures. One of the main problems associated to brain tumours is its infiltrative nature, which makes complete tumour resection a highly difficult task. With the combination of Hyperspectral Imaging and Machine Learning techniques, the project aimed at demonstrating that a precise determination of tumour boundaries was possible, helping this way neurosurgeons to minimize the amount of removed healthy tissue. The project partners involved, besides different universities and companies, two hospitals where the demonstrator was tested during surgical procedures. This paper introduces the difficulties around brain tumor resection, stating the main objectives of the project and presenting the materials, methodologies and platforms used to propose a solution. A brief summary of the main results obtained is also included.
HELICoiD:实时脑癌检测的跨学科合作项目:特邀论文
HELICoiD项目是欧洲FP7 FET Open资助的项目。它是生物医学领域边缘的一项跨学科工作,汇集了神经外科医生、计算机科学家和电子工程师。该项目的主要目标是提供术中图像引导手术系统的工作演示,用于实时脑癌检测,以便在肿瘤切除过程中协助神经外科医生。与脑肿瘤相关的主要问题之一是其浸润性,这使得完全切除肿瘤是一项非常困难的任务。通过结合高光谱成像和机器学习技术,该项目旨在证明精确确定肿瘤边界是可能的,从而帮助神经外科医生最大限度地减少切除健康组织的数量。除了不同的大学和公司外,项目合作伙伴还涉及两家医院,在那里演示器在手术过程中进行了测试。本文介绍了脑肿瘤切除的困难,说明了该项目的主要目标,并介绍了提出解决方案所使用的材料、方法和平台。本文还简要总结了所获得的主要结果。
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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