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MIPAR - A Science Gateway for Analyzing and Sharing Medical Images/Benjamin Aribisala

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Presentation during the 14th Association of African Universities (AAU) Conference and African Open Science Platform (AOSP)/Research Data Alliance (RDA) Workshop in Accra, Ghana, 7-8 June 2017.

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MIPAR - A Science Gateway for Analyzing and Sharing Medical Images/Benjamin Aribisala

  1. 1. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement n° 654237 MIPAR – A Science Gateway for Analyzing and Sharing Medical Images Benjamin Aribisala – Lagos State University - Nigeria (Benjamin.Aribisala@lasu.edu.ng)
  2. 2. Overview 2  Background  Scientific Problems  Aim and Benefits  What is MIPAR?  What can You use MIPAR for?  How to use MIPAR?  Future Plans and Conclusions
  3. 3. Background 3 • Medical images are images acquired from humans or animals • Medical images are used for clinical diagnosis, treatment and patient management. • There are many methods of acquiring medical images. Each method has specific use, strengths or weaknesses • Medical Image analysis and computer vision provide a platform for developing computational techniques for converting raw images to meaningful information.
  4. 4. Image Analysis Challenges in Africa 4 • Imaging equipment are very expensive • Image acquisition is very expensive • There are limited availability of medical image analysts in Africa • Limited collaboration efforts and ability to share expertise amongst clinical experts
  5. 5. Science Gateway Provides a Solution 5 • The advancements in internet technology, data communication and reduction in hardware cost has led to the birth of Science Gateway • Science Gateway can help in solving medical image analysis problems by offering tools for • Creating of image repositories • Making image analysis tools available • Making workflow available • Adapting some of the tools to make them intelligent • Science Gateway is in top gear in the developed world but very sluggish in Africa • In particular, there is no platform for image analysis in Africa
  6. 6. Aim and Benefits 6 To develop an e-infrastructure that will serve as a repository and an image processor for medical images It is our hope that the proposed platform could lead to • Improved and timely diagnosis • Improved patient management • Increased life expectancy • Better collaboration • Safes cost of travelling to see other experts AIM BENEFITS
  7. 7. What is MIPAR? 7  Medical Image Processor and Repository (MIPAR) is an e- infrastructure for sharing and analyzing medical images  The web address of MIPAR is https://mipar.sci-gaia.eu  MIPAR is one of the products of the collaboration between Lagos State University and SCI-GAIA  For More information, contact us at Benjamin.aribisala@lasu.edu.ng
  8. 8. Targeted Users 8 1. Clinicians 2. Researchers a. MSc / PhD / MD Students b. Faculty members 3. Anyone interested in analyzing medical images 4. Anyone interested collaborating with image analysts or clinicians
  9. 9. What Can Users Do With MIPAR? 9 • Donate Images for your research • Download Free images for your research • Process Images • Analyse images • Discuss a case report
  10. 10. What Can Users Do with MIPAR? 10 Donate Images Download Free Images Download outputs Process Images Registered user Image Types CT MRI Doppler Ultrasound Image Format .hdr/.img .nii .nii.gz (.zip) Anatomy Brain Liver Lung Chest Processes Brain Extraction Image Segmentation Image registration Analyze Images
  11. 11. System Requirements 11  Software Tools Used for Development  Futuregateway  OAR  PHP  JSON  WAMP  Software Requirement for users  Web browser  Internet  Windows operating system or mac  Hardware Requirement for users  Pentium 4, 4GB RAM, 500 GB disk space
  12. 12. Modules of MIPAR 12 Registration Download Images Process Images Donate Images Analyze Images
  13. 13. Impact of MIPAR 13 • Data Availability • Data Shareability • Collaboration • Reproducibility • Standardization • Educational benefits • Improved diagnosis and patient management
  14. 14. Medical Image Processor and Repository 14 Home Page https://mipar.sci-gaia.eu
  15. 15. Access through Federated Identity 15 Choose catch-all if in doubt
  16. 16. Registration using Federated Identity 16
  17. 17. MIPAR – Image donation (https://mipar.sci-gaia.eu) 17
  18. 18. MIPAR – Image search & download 18
  19. 19. MIPAR – Image search & download & visualise 19
  20. 20. MIPAR – Image processing (brain extraction, segmentation, etc.) 20
  21. 21. MIPAR – Processed Images (e.g. brain extraction and segmentation) 21
  22. 22. Analyze Module 22 • Perform Regression • Compute correlation • Compare two groups within a dataset • Compare two measurements within a dataset
  23. 23. Future Plans and Conclusions 23  We are currently seeking funds to:  publicize MIPAR  get data into MIPAR  MIPAR was tested with Brain MRI Data,  we need to include other imaging modalities  We also need to include other anatomies  With MIPAR you can share, process and analyse medical images  If you have medical images or you have a colleague who has some, please talk to us, Benjamin.Aribisala@lasu.edu.ng Future Plans Conclusion
  24. 24. How Does MIPAR Align with the Four themes of the African Open Science Platform 24
  25. 25. AOSP Themes 25 • Policy. The benefits of MIPAR could help to formulate policy in the area of openness, collaboration, data sharing and data use • Infrastructure. MIPAR is an e-infrastructure. So it makes infrastructure available for the public • Capacity Building. Training – BSc, MSc, PhD, Faculty • Incentives. MIPAR has started to motivate similar projects, collaborations and Lagos Hackfest
  26. 26. Appreciations 26 MIPAR Team 1.Roberto Barbera, sci-gaia 2.Simon Taylor, sci-gaia 3.Benjamin Aribisala 4.Bruce Becker, sci-gaia 5.Olabanjo Olusola 6.Mario Torris 7.Rita Ricceri 8.Riccardo Bruno A big appreciation to the co-funders - SCI-GAIA, INDIGO-DATACLOUD AND ENEL We appreciate Eko-Konnect and WACREN for establishing a link between Lagos State University and SCI-GAIA We appreciate AOSP, CODATA, RDA and AAU AOSP Team 1.Ina Smith 2.Nozuko Hlwatika 3.Susan Vledsman 4.Simon Hodson

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