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

Published: 15 May 2017 Publication History

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.

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Cited By

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  • (2020)Classification of Hyperspectral In Vivo Brain Tissue Based on Linear UnmixingApplied Sciences10.3390/app1016568610:16(5686)Online publication date: 17-Aug-2020
  • (2020)Regulated Power Supply with High Power Factor for Hyperspectral Imaging Applications2020 XIV Technologies Applied to Electronics Teaching Conference (TAEE)10.1109/TAEE46915.2020.9163660(1-7)Online publication date: Jul-2020
  • (2019)In-Vivo and Ex-Vivo Tissue Analysis through Hyperspectral Imaging Techniques: Revealing the Invisible Features of CancerCancers10.3390/cancers1106075611:6(756)Online publication date: 30-May-2019
  • Show More Cited By

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cover image ACM Conferences
CF'17: Proceedings of the Computing Frontiers Conference
May 2017
450 pages
ISBN:9781450344876
DOI:10.1145/3075564
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 15 May 2017

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Author Tags

  1. brain cancer detection
  2. hyperspectral image processing
  3. image-guided surgery
  4. supervised classification
  5. unsupervised clustering

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CF '17: Computing Frontiers Conference
May 15 - 17, 2017
Siena, Italy

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CF'17 Paper Acceptance Rate 43 of 87 submissions, 49%;
Overall Acceptance Rate 273 of 785 submissions, 35%

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Cited By

View all
  • (2020)Classification of Hyperspectral In Vivo Brain Tissue Based on Linear UnmixingApplied Sciences10.3390/app1016568610:16(5686)Online publication date: 17-Aug-2020
  • (2020)Regulated Power Supply with High Power Factor for Hyperspectral Imaging Applications2020 XIV Technologies Applied to Electronics Teaching Conference (TAEE)10.1109/TAEE46915.2020.9163660(1-7)Online publication date: Jul-2020
  • (2019)In-Vivo and Ex-Vivo Tissue Analysis through Hyperspectral Imaging Techniques: Revealing the Invisible Features of CancerCancers10.3390/cancers1106075611:6(756)Online publication date: 30-May-2019
  • (2018)Accelerating the K-Nearest Neighbors Filtering Algorithm to Optimize the Real-Time Classification of Human Brain Tumor in Hyperspectral ImagesSensors10.3390/s1807231418:7(2314)Online publication date: 17-Jul-2018
  • (2018)An Intraoperative Visualization System Using Hyperspectral Imaging to Aid in Brain Tumor DelineationSensors10.3390/s1802043018:2(430)Online publication date: 1-Feb-2018
  • (2018)Machine Intelligence in Healthcare and Medical Cyber Physical Systems: A SurveyIEEE Access10.1109/ACCESS.2018.28660496(46419-46494)Online publication date: 2018

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