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Segmentation and immersive visualization of brain lesions using deep learning and virtual reality

dc.contributor.authorKelley, Brendan, author
dc.contributor.authorPlabst, Lucas, author
dc.contributor.authorPlabst, Lena, author
dc.contributor.authorACM, publisher
dc.date.accessioned2025-03-13T18:31:29Z
dc.date.available2025-03-13T18:31:29Z
dc.date.issued2025-01-19
dc.description.abstractMagnetic resonance imaging (MRIs) are commonly used for diagnosing potential neurological disorders, however preparation and interpretation of MRI scans requires professional oversight. Additionally, MRIs are typically viewed as single cross sections of the affected regions which does not always capture the full picture of brain lesions and can be difficult to understand due to 2D's inherent abstraction of our 3D world. To address these challenges we propose a immersive visualization pipeline that combines deep learning image segmentation techniques using a VGG-16 model trained on MRI fluid attenuated inversion recovery (FLAIR) with virtual reality (VR) immersive analytics. Our visualization pipeline begins with our VGG-16 model predicting which regions of the brain are potentially affected by a disease. This output, along with the original scan, are then volumentrically rendered. These renders can then be viewed in VR using an head mounted display (HMD). Within the HMD users can move through the volumentric renderings to view the affected regions and utilize planes to view cross sections of the MRI scans. Our work provides a potential pipeline and tool for diagnosis and care.
dc.format.mediumborn digital
dc.format.mediumarticles
dc.identifier.bibliographicCitationBrendan Kelley, Lucas Plabst, and Lena Plabst. 2024. Segmentation and Immersive Visualization of Brain Lesions Using Deep Learning and Virtual Reality. In The 19th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry (VRCAI 24), December 01 02, 2024, Nanjing, China. ACM, New York, NY, USA, 8 pages. https://doi.org/10.1145/3703619.3706035
dc.identifier.doihttps://doi.org/10.1145/3703619.3706035
dc.identifier.urihttps://hdl.handle.net/10217/240172
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofPublications
dc.relation.ispartofACM DL Digital Library
dc.rights©Brendan Kelley, et al. ACM 2024. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in VRCAI 24, https://dx.doi.org/10.1145/3703619.3706035.
dc.subjectdeep learning
dc.subjectimage segmentation
dc.subjectmedical imaging
dc.subjectmedical applications
dc.subjectvirtual reality
dc.subjectimmersive analytics
dc.subjectimmersive visualization
dc.titleSegmentation and immersive visualization of brain lesions using deep learning and virtual reality
dc.typeText

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