Integration of a web-based Magnetic Resonance Imaging visualization tool
This thesis explores the integration of a web-based MRI visualization tool, MRIViewer, into the AI-Epilepsy platform to enhance the diagnosis of refractory epilepsy. The project focuses on creating a seamless and user-friendly experience for medical professionals. Key success criteria include displa...
- Autores:
-
Granada Martínez, Diego
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2024
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/73958
- Acceso en línea:
- https://hdl.handle.net/1992/73958
- Palabra clave:
- Mri
react
dicom
visualization
Ingeniería
- Rights
- openAccess
- License
- Attribution 4.0 International
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Integration of a web-based Magnetic Resonance Imaging visualization tool |
| title |
Integration of a web-based Magnetic Resonance Imaging visualization tool |
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Integration of a web-based Magnetic Resonance Imaging visualization tool Mri react dicom visualization Ingeniería |
| title_short |
Integration of a web-based Magnetic Resonance Imaging visualization tool |
| title_full |
Integration of a web-based Magnetic Resonance Imaging visualization tool |
| title_fullStr |
Integration of a web-based Magnetic Resonance Imaging visualization tool |
| title_full_unstemmed |
Integration of a web-based Magnetic Resonance Imaging visualization tool |
| title_sort |
Integration of a web-based Magnetic Resonance Imaging visualization tool |
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Granada Martínez, Diego |
| dc.contributor.advisor.none.fl_str_mv |
Garcés Pernett, Kelly Johany Duitama Castellanos, Jorge Alexander |
| dc.contributor.author.none.fl_str_mv |
Granada Martínez, Diego |
| dc.subject.keyword.none.fl_str_mv |
Mri react dicom |
| topic |
Mri react dicom visualization Ingeniería |
| dc.subject.keyword.eng.fl_str_mv |
visualization |
| dc.subject.themes.spa.fl_str_mv |
Ingeniería |
| description |
This thesis explores the integration of a web-based MRI visualization tool, MRIViewer, into the AI-Epilepsy platform to enhance the diagnosis of refractory epilepsy. The project focuses on creating a seamless and user-friendly experience for medical professionals. Key success criteria include displaying continuous series of DICOM files, remote image loading and support for switching between multiple axes. The chosen solution, MRIViewer, is a modern React-based tool with Apache 2.0 licensing and features necessary for the project. The development methodology involves non-destructive changes to the existing codebase, ensuring compatibility with AI-Epilepsy’s technology stack. The prototype phase included transforming MRIViewer into a portable React component, creating a backend prototype for image downloading, and successful integration into the AI-Epilepsy platform. While primary requirements have been met, future improvements such as displaying multiple series simultaneously, annotating images with persistence, addressing flickering issues, and enhancing the user interface are changes identified for further development. |
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2024 |
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2024-02-08T16:39:56Z |
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2024-02-08T16:39:56Z |
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2024-02-07 |
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Trabajo de grado - Pregrado |
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info:eu-repo/semantics/bachelorThesis |
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https://hdl.handle.net/1992/73958 |
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eng |
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eng |
| dc.relation.references.none.fl_str_mv |
Andersen, L. S. (n.d.). Magnetic Resonance explained. Retrieved September 4, 2023, from https://www.drcmr.dk/MR Engel, J. (2014). Approaches to refractory epilepsy. Annals of Indian Academy of Neurology, 17(Suppl 1), S12–S17. https://doi.org/10.4103/0972-2327.128644 EPAM. (2023). MRI Viewer: Medical image 2D/3D web viewer. [original-date: 2017-12-11T09:06:58Z]. Retrieved September 6, 2023, from https://github.com/epam/mriviewer Innolitics. (2023). Study ID Attribute – DICOM Standard Browser. Retrieved November 7,2023, from https://dicom.innolitics.com/ciods/mr-image/general-study/00200010 John Hopkins. (2023). Magnetic Resonance Imaging (MRI). Retrieved September 4, 2023, from https://www.hopkinsmedicine.org/health/treatment-tests-and-therapies/magnetic-resonance-imaging-mri Larobina, M., & Murino, L. (2014). Medical Image File Formats. Journal of Digital Imaging, 27(2), 200–206. https://doi.org/10.1007/s10278-013-9657-9 Mount Sinai. (n.d.). Epilepsy - overview Information | Mount Sinai - New York. Retrieved September 4, 2023, from https://www.mountsinai.org/health-library/diseases-conditions/epilepsy-overview Nishimura, D. G. (2010). Principles of Magnetic Resonance Imaging. Stanford Univ. https://www.amazon.com/Principles-Magnetic-Resonance-Imaging-Nishimura/dp/B0006S4BE2 Padmanaban, S., Thiruvenkadam, K., T., P., Thirumalaiselvi, M., & Sivasakthivel, R. (2020). A Role of Medical Imaging Techniques in Human Brain Tumor Treatment. 8, 565–568. https://doi.org/10.35940/ijrte.D1105.1284S219 Real Engineering. (2023). The Insane Engineering of MRI Machines. Retrieved September 4, 2023, from https://www.youtube.com/watch?v=NlYXqRG7lus RII-Mango. (2023). Daikon [original-date: 2015-03-10T18:44:03Z]. Retrieved August 16, 2023, from https://github.com/rii-mango/Daikon Sinai, M. (n.d.). Seizures Information | Mount Sinai - New York. Retrieved September 2, 2023, from https://www.mountsinai.org/health-library/symptoms/seizures Slice:Drop. (2023). Slice:Drop. Retrieved August 12, 2023, from https://slicedrop.com/ The X Toolkit Developers. (2023). GitHub - xtk/X: The X Toolkit. Retrieved August 12, 2023, from https://github.com/xtk/X#readme WHO. (2023). Epilepsy. Retrieved September 4, 2023, from https://www.who.int/news-room/fact-sheets/detail/epilepsy |
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Attribution 4.0 International |
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openAccess |
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37 páginas |
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application/pdf |
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Universidad de los Andes |
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Ingeniería de Sistemas y Computación |
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Facultad de Ingeniería |
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Departamento de Ingeniería Sistemas y Computación |
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Universidad de los Andes |
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Garcés Pernett, Kelly Johanyvirtual::410-1Duitama Castellanos, Jorge Alexandervirtual::415-1Granada Martínez, Diego2024-02-08T16:39:56Z2024-02-08T16:39:56Z2024-02-07https://hdl.handle.net/1992/73958instname:Universidad de los Andesreponame:Repositorio Institucional Sénecarepourl:https://repositorio.uniandes.edu.co/This thesis explores the integration of a web-based MRI visualization tool, MRIViewer, into the AI-Epilepsy platform to enhance the diagnosis of refractory epilepsy. The project focuses on creating a seamless and user-friendly experience for medical professionals. Key success criteria include displaying continuous series of DICOM files, remote image loading and support for switching between multiple axes. The chosen solution, MRIViewer, is a modern React-based tool with Apache 2.0 licensing and features necessary for the project. The development methodology involves non-destructive changes to the existing codebase, ensuring compatibility with AI-Epilepsy’s technology stack. The prototype phase included transforming MRIViewer into a portable React component, creating a backend prototype for image downloading, and successful integration into the AI-Epilepsy platform. While primary requirements have been met, future improvements such as displaying multiple series simultaneously, annotating images with persistence, addressing flickering issues, and enhancing the user interface are changes identified for further development.Ingeniero de Sistemas y ComputaciónPregrado37 páginasapplication/pdfengUniversidad de los AndesIngeniería de Sistemas y ComputaciónFacultad de IngenieríaDepartamento de Ingeniería Sistemas y ComputaciónAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Integration of a web-based Magnetic Resonance Imaging visualization toolTrabajo de grado - Pregradoinfo:eu-repo/semantics/bachelorThesisinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_7a1fTexthttp://purl.org/redcol/resource_type/TPMrireactdicomvisualizationIngenieríaAndersen, L. S. (n.d.). Magnetic Resonance explained. Retrieved September 4, 2023, from https://www.drcmr.dk/MREngel, J. (2014). Approaches to refractory epilepsy. Annals of Indian Academy of Neurology, 17(Suppl 1), S12–S17. https://doi.org/10.4103/0972-2327.128644EPAM. (2023). MRI Viewer: Medical image 2D/3D web viewer. [original-date: 2017-12-11T09:06:58Z]. Retrieved September 6, 2023, from https://github.com/epam/mriviewerInnolitics. (2023). Study ID Attribute – DICOM Standard Browser. Retrieved November 7,2023, from https://dicom.innolitics.com/ciods/mr-image/general-study/00200010John Hopkins. (2023). Magnetic Resonance Imaging (MRI). Retrieved September 4, 2023, from https://www.hopkinsmedicine.org/health/treatment-tests-and-therapies/magnetic-resonance-imaging-mriLarobina, M., & Murino, L. (2014). Medical Image File Formats. Journal of Digital Imaging, 27(2), 200–206. https://doi.org/10.1007/s10278-013-9657-9Mount Sinai. (n.d.). Epilepsy - overview Information | Mount Sinai - New York. Retrieved September 4, 2023, from https://www.mountsinai.org/health-library/diseases-conditions/epilepsy-overviewNishimura, D. G. (2010). Principles of Magnetic Resonance Imaging. Stanford Univ. https://www.amazon.com/Principles-Magnetic-Resonance-Imaging-Nishimura/dp/B0006S4BE2Padmanaban, S., Thiruvenkadam, K., T., P., Thirumalaiselvi, M., & Sivasakthivel, R. (2020). A Role of Medical Imaging Techniques in Human Brain Tumor Treatment. 8, 565–568. https://doi.org/10.35940/ijrte.D1105.1284S219Real Engineering. (2023). The Insane Engineering of MRI Machines. Retrieved September 4, 2023, from https://www.youtube.com/watch?v=NlYXqRG7lusRII-Mango. (2023). Daikon [original-date: 2015-03-10T18:44:03Z]. Retrieved August 16, 2023, from https://github.com/rii-mango/DaikonSinai, M. (n.d.). Seizures Information | Mount Sinai - New York. Retrieved September 2, 2023, from https://www.mountsinai.org/health-library/symptoms/seizuresSlice:Drop. (2023). Slice:Drop. Retrieved August 12, 2023, from https://slicedrop.com/The X Toolkit Developers. (2023). GitHub - xtk/X: The X Toolkit. Retrieved August 12, 2023, from https://github.com/xtk/X#readmeWHO. (2023). Epilepsy. 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